Overview

Brought to you by YData

Dataset statistics

Number of variables	94
Number of observations	512
Missing cells	43330
Missing cells (%)	90.0%
Duplicate rows	1
Duplicate rows (%)	0.2%
Total size in memory	979.2 KiB
Average record size in memory	1.9 KiB

Variable types

Numeric	20
Categorical	35
Text	21
Unsupported	8
DateTime	10

Alerts

`privilege_id` has constant value "2"	Constant
`business_phone` has constant value "(123)555-0100"	Constant
`home_phone` has constant value "(123)555-0102"	Constant
`zip_postal_code` has constant value "99999"	Constant
`country_region` has constant value "USA"	Constant
`attachments` has constant value ""	Constant
`tax` has constant value "0.0"	Constant
`shipping` has constant value "0.0"	Constant
`amount_due` has constant value "0.0"	Constant
`discount` has constant value "0.0"	Constant
`ship_zip_postal_code` has constant value "99999"	Constant
`ship_country_region` has constant value "USA"	Constant
`taxes` has constant value "0.0"	Constant
`tax_rate` has constant value "0.0"	Constant
`privilege_name` has constant value "Purchase Approvals"	Constant
`discontinued` has constant value "0"	Constant
`payment_amount` has constant value "0.0"	Constant
`payment_method` has constant value "Check"	Constant
`approved_by` has constant value "2"	Constant
Dataset has 1 (0.2%) duplicate rows	Duplicates
`__table_name__` is highly overall correlated with `category` and 30 other fields	High correlation
`category` is highly overall correlated with `__table_name__` and 1 other fields	High correlation
`city` is highly overall correlated with `fax_number` and 2 other fields	High correlation
`created_by` is highly overall correlated with `__table_name__` and 1 other fields	High correlation
`customer_id` is highly overall correlated with `__table_name__` and 5 other fields	High correlation
`default` is highly overall correlated with `__table_name__`	High correlation
`fax_number` is highly overall correlated with `__table_name__` and 5 other fields	High correlation
`id` is highly overall correlated with `__table_name__` and 10 other fields	High correlation
`inventory_id` is highly overall correlated with `__table_name__` and 3 other fields	High correlation
`job_title` is highly overall correlated with `__table_name__` and 2 other fields	High correlation
`list_price` is highly overall correlated with `__table_name__` and 2 other fields	High correlation
`minimum_reorder_quantity` is highly overall correlated with `__table_name__` and 2 other fields	High correlation
`order_id` is highly overall correlated with `id` and 2 other fields	High correlation
`payment_type` is highly overall correlated with `__table_name__` and 5 other fields	High correlation
`posted_to_inventory` is highly overall correlated with `__table_name__` and 2 other fields	High correlation
`purchase_order_id` is highly overall correlated with `__table_name__` and 3 other fields	High correlation
`reorder_level` is highly overall correlated with `__table_name__` and 2 other fields	High correlation
`ship_address` is highly overall correlated with `__table_name__` and 7 other fields	High correlation
`ship_city` is highly overall correlated with `__table_name__` and 7 other fields	High correlation
`ship_name` is highly overall correlated with `__table_name__` and 7 other fields	High correlation
`ship_state_province` is highly overall correlated with `__table_name__` and 7 other fields	High correlation
`shipper_id` is highly overall correlated with `__table_name__` and 4 other fields	High correlation
`shipping_fee` is highly overall correlated with `id` and 4 other fields	High correlation
`standard_cost` is highly overall correlated with `__table_name__` and 2 other fields	High correlation
`state_province` is highly overall correlated with `__table_name__` and 4 other fields	High correlation
`status_id` is highly overall correlated with `__table_name__`	High correlation
`string_id` is highly overall correlated with `__table_name__`	High correlation
`submitted_by` is highly overall correlated with `__table_name__` and 1 other fields	High correlation
`supplier_id` is highly overall correlated with `__table_name__`	High correlation
`supplier_ids` is highly overall correlated with `__table_name__` and 1 other fields	High correlation
`target_level` is highly overall correlated with `__table_name__` and 2 other fields	High correlation
`transaction_type` is highly overall correlated with `__table_name__` and 1 other fields	High correlation
`unit_cost` is highly overall correlated with `__table_name__`	High correlation
`unit_price` is highly overall correlated with `__table_name__`	High correlation
`web_page` is highly overall correlated with `__table_name__` and 3 other fields	High correlation
`employee_id` has 463 (90.4%) missing values	Missing
`privilege_id` has 511 (99.8%) missing values	Missing
`id` has 68 (13.3%) missing values	Missing
`company` has 460 (89.8%) missing values	Missing
`last_name` has 463 (90.4%) missing values	Missing
`first_name` has 463 (90.4%) missing values	Missing
`email_address` has 503 (98.2%) missing values	Missing
`job_title` has 463 (90.4%) missing values	Missing
`business_phone` has 473 (92.4%) missing values	Missing
`home_phone` has 503 (98.2%) missing values	Missing
`mobile_phone` has 512 (100.0%) missing values	Missing
`fax_number` has 473 (92.4%) missing values	Missing
`address` has 470 (91.8%) missing values	Missing
`city` has 470 (91.8%) missing values	Missing
`state_province` has 470 (91.8%) missing values	Missing
`zip_postal_code` has 470 (91.8%) missing values	Missing
`country_region` has 470 (91.8%) missing values	Missing
`web_page` has 503 (98.2%) missing values	Missing
`notes` has 490 (95.7%) missing values	Missing
`attachments` has 415 (81.1%) missing values	Missing
`type_name` has 508 (99.2%) missing values	Missing
`transaction_type` has 410 (80.1%) missing values	Missing
`transaction_created_date` has 410 (80.1%) missing values	Missing
`transaction_modified_date` has 410 (80.1%) missing values	Missing
`product_id` has 297 (58.0%) missing values	Missing
`quantity` has 297 (58.0%) missing values	Missing
`purchase_order_id` has 442 (86.3%) missing values	Missing
`customer_order_id` has 512 (100.0%) missing values	Missing
`comments` has 498 (97.3%) missing values	Missing
`order_id` has 419 (81.8%) missing values	Missing
`invoice_date` has 477 (93.2%) missing values	Missing
`due_date` has 512 (100.0%) missing values	Missing
`tax` has 477 (93.2%) missing values	Missing
`shipping` has 477 (93.2%) missing values	Missing
`amount_due` has 477 (93.2%) missing values	Missing
`unit_price` has 454 (88.7%) missing values	Missing
`discount` has 454 (88.7%) missing values	Missing
`status_id` has 378 (73.8%) missing values	Missing
`date_allocated` has 512 (100.0%) missing values	Missing
`inventory_id` has 413 (80.7%) missing values	Missing
`status` has 502 (98.0%) missing values	Missing
`customer_id` has 464 (90.6%) missing values	Missing
`order_date` has 464 (90.6%) missing values	Missing
`shipped_date` has 473 (92.4%) missing values	Missing
`shipper_id` has 469 (91.6%) missing values	Missing
`ship_name` has 464 (90.6%) missing values	Missing
`ship_address` has 464 (90.6%) missing values	Missing
`ship_city` has 464 (90.6%) missing values	Missing
`ship_state_province` has 464 (90.6%) missing values	Missing
`ship_zip_postal_code` has 464 (90.6%) missing values	Missing
`ship_country_region` has 464 (90.6%) missing values	Missing
`shipping_fee` has 436 (85.2%) missing values	Missing
`taxes` has 436 (85.2%) missing values	Missing
`payment_type` has 474 (92.6%) missing values	Missing
`paid_date` has 474 (92.6%) missing values	Missing
`tax_rate` has 464 (90.6%) missing values	Missing
`tax_status_id` has 512 (100.0%) missing values	Missing
`status_name` has 508 (99.2%) missing values	Missing
`tax_status_name` has 510 (99.6%) missing values	Missing
`privilege_name` has 511 (99.8%) missing values	Missing
`supplier_ids` has 467 (91.2%) missing values	Missing
`product_code` has 467 (91.2%) missing values	Missing
`product_name` has 467 (91.2%) missing values	Missing
`description` has 512 (100.0%) missing values	Missing
`standard_cost` has 467 (91.2%) missing values	Missing
`list_price` has 467 (91.2%) missing values	Missing
`reorder_level` has 467 (91.2%) missing values	Missing
`target_level` has 467 (91.2%) missing values	Missing
`quantity_per_unit` has 472 (92.2%) missing values	Missing
`discontinued` has 467 (91.2%) missing values	Missing
`minimum_reorder_quantity` has 482 (94.1%) missing values	Missing
`category` has 467 (91.2%) missing values	Missing
`unit_cost` has 457 (89.3%) missing values	Missing
`date_received` has 469 (91.6%) missing values	Missing
`posted_to_inventory` has 457 (89.3%) missing values	Missing
`supplier_id` has 484 (94.5%) missing values	Missing
`created_by` has 487 (95.1%) missing values	Missing
`submitted_date` has 484 (94.5%) missing values	Missing
`creation_date` has 484 (94.5%) missing values	Missing
`expected_date` has 512 (100.0%) missing values	Missing
`payment_date` has 512 (100.0%) missing values	Missing
`payment_amount` has 484 (94.5%) missing values	Missing
`payment_method` has 510 (99.6%) missing values	Missing
`approved_by` has 487 (95.1%) missing values	Missing
`approved_date` has 487 (95.1%) missing values	Missing
`submitted_by` has 484 (94.5%) missing values	Missing
`group_by` has 507 (99.0%) missing values	Missing
`display` has 507 (99.0%) missing values	Missing
`title` has 507 (99.0%) missing values	Missing
`filter_row_source` has 507 (99.0%) missing values	Missing
`default` has 507 (99.0%) missing values	Missing
`string_id` has 450 (87.9%) missing values	Missing
`string_data` has 450 (87.9%) missing values	Missing
`mobile_phone` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`customer_order_id` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`due_date` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`date_allocated` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`tax_status_id` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`description` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`expected_date` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`payment_date` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`shipping_fee` has 40 (7.8%) zeros	Zeros

Reproduction

Analysis started	2025-10-30 16:21:44.370986
Analysis finished	2025-10-30 16:23:00.401455
Duration	1 minute and 16.03 seconds
Software version	ydata-profiling vv4.17.0
Download configuration	config.json

employee_id
Real number (ℝ)

Missing

Distinct	8
Distinct (%)	16.3%
Missing	463
Missing (%)	90.4%
Infinite	0
Infinite (%)	0.0%
Mean	4.4081633

Minimum	1
Maximum	9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	4
Q3	7
95-th percentile	9
Maximum	9
Range	8
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.0339631
Coefficient of variation (CV)	0.68826014
Kurtosis	-1.3286551
Mean	4.4081633
Median Absolute Deviation (MAD)	3
Skewness	0.42747153
Sum	216
Variance	9.204932
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
1	12	2.3%
9	10	2.0%
4	8	1.6%
3	6	1.2%
2	5	1.0%
6	4	0.8%
8	2	0.4%
7	2	0.4%
(Missing)	463	90.4%

Value	Count	Frequency (%)
1	12	2.3%
2	5	1.0%
3	6	1.2%
4	8	1.6%
6	4	0.8%
7	2	0.4%
8	2	0.4%
9	10	2.0%

Value	Count	Frequency (%)
9	10	2.0%
8	2	0.4%
7	2	0.4%
6	4	0.8%
4	8	1.6%
3	6	1.2%
2	5	1.0%
1	12	2.3%

privilege_id
Categorical

Constant Missing

Distinct	1
Distinct (%)	100.0%
Missing	511
Missing (%)	99.8%
Memory size	28.1 KiB

2	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	100.0%

Sample

1st row	2

Common Values

Value	Count	Frequency (%)
2	1	0.2%
(Missing)	511	99.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2	1	100.0%

Most occurring characters

Value	Count	Frequency (%)
2	1	100.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
2	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
2	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
2	1	100.0%

__table_name__
Categorical

High correlation

Distinct	20
Distinct (%)	3.9%
Missing	0
Missing (%)	0.0%
Memory size	35.4 KiB

inventory_transactions	102
strings	62
order_details	58
purchase_order_details	55
orders	48
Other values (15)	187

Length

Max length	27
Median length	22
Mean length	13.509766
Min length	6

Characters and Unicode

Total characters	6917
Distinct characters	20
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	0.4%

Sample

1st row	employee_privileges
2nd row	employees
3rd row	employees
4th row	employees
5th row	employees

Common Values

Value	Count	Frequency (%)
inventory_transactions	102	19.9%
strings	62	12.1%
order_details	58	11.3%
purchase_order_details	55	10.7%
orders	48	9.4%
products	45	8.8%
invoices	35	6.8%
customer	30	5.9%
purchase_orders	28	5.5%
suppliers	10	2.0%
Other values (10)	39	7.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
inventory_transactions	102	19.9%
strings	62	12.1%
order_details	58	11.3%
purchase_order_details	55	10.7%
orders	48	9.4%
products	45	8.8%
invoices	35	6.8%
customer	30	5.9%
purchase_orders	28	5.5%
suppliers	10	2.0%
Other values (10)	39	7.6%

Most occurring characters

Value	Count	Frequency (%)
r	871	12.6%
s	818	11.8%
e	643	9.3%
t	617	8.9%
o	542	7.8%
n	521	7.5%
i	480	6.9%
a	441	6.4%
d	369	5.3%
_	340	4.9%
Other values (10)	1275	18.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	6917	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
r	871	12.6%
s	818	11.8%
e	643	9.3%
t	617	8.9%
o	542	7.8%
n	521	7.5%
i	480	6.9%
a	441	6.4%
d	369	5.3%
_	340	4.9%
Other values (10)	1275	18.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	6917	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
r	871	12.6%
s	818	11.8%
e	643	9.3%
t	617	8.9%
o	542	7.8%
n	521	7.5%
i	480	6.9%
a	441	6.4%
d	369	5.3%
_	340	4.9%
Other values (10)	1275	18.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	6917	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
r	871	12.6%
s	818	11.8%
e	643	9.3%
t	617	8.9%
o	542	7.8%
n	521	7.5%
i	480	6.9%
a	441	6.4%
d	369	5.3%
_	340	4.9%
Other values (10)	1275	18.4%

id
Real number (ℝ)

High correlation Missing

Distinct	198
Distinct (%)	44.6%
Missing	68
Missing (%)	13.3%
Infinite	0
Infinite (%)	0.0%
Mean	81.867117

Minimum	0
Maximum	295
Zeros	4
Zeros (%)	0.8%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	0
5-th percentile	2
Q1	29
median	63
Q3	99
95-th percentile	269.85
Maximum	295
Range	295
Interquartile range (IQR)	70

Descriptive statistics

Standard deviation	78.011679
Coefficient of variation (CV)	0.95290614
Kurtosis	1.2419314
Mean	81.867117
Median Absolute Deviation (MAD)	35
Skewness	1.4472114
Sum	36349
Variance	6085.822
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	11	2.1%
3	9	1.8%
2	9	1.8%
4	6	1.2%
5	6	1.2%
7	5	1.0%
6	5	1.0%
8	5	1.0%
36	4	0.8%
9	4	0.8%
Other values (188)	380	74.2%
(Missing)	68	13.3%

Value	Count	Frequency (%)
0	4	0.8%
1	11	2.1%
2	9	1.8%
3	9	1.8%
4	6	1.2%
5	6	1.2%
6	5	1.0%
7	5	1.0%
8	5	1.0%
9	4	0.8%

Value	Count	Frequency (%)
295	1	0.2%
294	1	0.2%
293	1	0.2%
292	1	0.2%
290	1	0.2%
289	1	0.2%
288	1	0.2%
286	1	0.2%
285	1	0.2%
283	1	0.2%

company
Text

Missing

Distinct	43
Distinct (%)	82.7%
Missing	460
Missing (%)	89.8%
Memory size	18.0 KiB

Length

Max length	18
Median length	9
Mean length	11.153846
Min length	9

Characters and Unicode

Total characters	580
Distinct characters	44
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	41 ?
Unique (%)	78.8%

Sample

1st row	Northwind Traders
2nd row	Northwind Traders
3rd row	Northwind Traders
4th row	Northwind Traders
5th row	Northwind Traders

Value	Count	Frequency (%)
company	33	30.8%
supplier	10	9.3%
traders	9	8.4%
northwind	9	8.4%
a	4	3.7%
shipping	3	2.8%
c	3	2.8%
b	3	2.8%
d	2	1.9%
f	2	1.9%
Other values (24)	29	27.1%

Most occurring characters

Value	Count	Frequency (%)
p	59	10.2%
	55	9.5%
n	45	7.8%
o	42	7.2%
a	42	7.2%
C	38	6.6%
r	37	6.4%
y	33	5.7%
m	33	5.7%
i	25	4.3%
Other values (34)	171	29.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	580	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
p	59	10.2%
	55	9.5%
n	45	7.8%
o	42	7.2%
a	42	7.2%
C	38	6.6%
r	37	6.4%
y	33	5.7%
m	33	5.7%
i	25	4.3%
Other values (34)	171	29.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	580	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
p	59	10.2%
	55	9.5%
n	45	7.8%
o	42	7.2%
a	42	7.2%
C	38	6.6%
r	37	6.4%
y	33	5.7%
m	33	5.7%
i	25	4.3%
Other values (34)	171	29.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	580	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
p	59	10.2%
	55	9.5%
n	45	7.8%
o	42	7.2%
a	42	7.2%
C	38	6.6%
r	37	6.4%
y	33	5.7%
m	33	5.7%
i	25	4.3%
Other values (34)	171	29.5%

last_name
Text

Missing

Distinct	46
Distinct (%)	93.9%
Missing	463
Missing (%)	90.4%
Memory size	17.7 KiB

Length

Max length	20
Median length	13
Mean length	7.0204082
Min length	2

Characters and Unicode

Total characters	344
Distinct characters	48
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	43 ?
Unique (%)	87.8%

Sample

1st row	Giussani
2nd row	Thorpe
3rd row	Zare
4th row	Freehafer
5th row	Neipper

Value	Count	Frequency (%)
andersen	2	3.9%
lee	2	3.9%
bedecs	2	3.9%
freehafer	1	2.0%
zare	1	2.0%
giussani	1	2.0%
kotas	1	2.0%
sergienko	1	2.0%
hellung-larsen	1	2.0%
cencini	1	2.0%
Other values (38)	38	74.5%

Most occurring characters

Value	Count	Frequency (%)
e	47	13.7%
a	31	9.0%
n	27	7.8%
r	25	7.3%
s	20	5.8%
o	19	5.5%
i	18	5.2%
l	14	4.1%
d	12	3.5%
c	10	2.9%
Other values (38)	121	35.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	344	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	47	13.7%
a	31	9.0%
n	27	7.8%
r	25	7.3%
s	20	5.8%
o	19	5.5%
i	18	5.2%
l	14	4.1%
d	12	3.5%
c	10	2.9%
Other values (38)	121	35.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	344	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	47	13.7%
a	31	9.0%
n	27	7.8%
r	25	7.3%
s	20	5.8%
o	19	5.5%
i	18	5.2%
l	14	4.1%
d	12	3.5%
c	10	2.9%
Other values (38)	121	35.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	344	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	47	13.7%
a	31	9.0%
n	27	7.8%
r	25	7.3%
s	20	5.8%
o	19	5.5%
i	18	5.2%
l	14	4.1%
d	12	3.5%
c	10	2.9%
Other values (38)	121	35.2%

first_name
Text

Missing

Distinct	46
Distinct (%)	93.9%
Missing	463
Missing (%)	90.4%
Memory size	17.6 KiB

Length

Max length	13
Median length	9
Mean length	6.4285714
Min length	3

Characters and Unicode

Total characters	315
Distinct characters	44
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	43 ?
Unique (%)	87.8%

Sample

1st row	Laura
2nd row	Steven
3rd row	Robert
4th row	Nancy
5th row	Michael

Value	Count	Frequency (%)
michael	2	3.8%
john	2	3.8%
anna	2	3.8%
elizabeth	2	3.8%
robert	1	1.9%
laura	1	1.9%
mariya	1	1.9%
andrew	1	1.9%
steven	1	1.9%
anne	1	1.9%
Other values (39)	39	73.6%

Most occurring characters

Value	Count	Frequency (%)
a	39	12.4%
n	37	11.7%
e	31	9.8%
i	23	7.3%
r	20	6.3%
o	16	5.1%
l	14	4.4%
t	13	4.1%
h	11	3.5%
A	10	3.2%
Other values (34)	101	32.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	315	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	39	12.4%
n	37	11.7%
e	31	9.8%
i	23	7.3%
r	20	6.3%
o	16	5.1%
l	14	4.4%
t	13	4.1%
h	11	3.5%
A	10	3.2%
Other values (34)	101	32.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	315	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	39	12.4%
n	37	11.7%
e	31	9.8%
i	23	7.3%
r	20	6.3%
o	16	5.1%
l	14	4.4%
t	13	4.1%
h	11	3.5%
A	10	3.2%
Other values (34)	101	32.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	315	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	39	12.4%
n	37	11.7%
e	31	9.8%
i	23	7.3%
r	20	6.3%
o	16	5.1%
l	14	4.4%
t	13	4.1%
h	11	3.5%
A	10	3.2%
Other values (34)	101	32.1%

email_address
Text

Missing

Distinct	9
Distinct (%)	100.0%
Missing	503
Missing (%)	98.2%
Memory size	16.6 KiB

Length

Max length	28
Median length	27
Mean length	26.333333
Min length	24

Characters and Unicode

Total characters	237
Distinct characters	21
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	9 ?
Unique (%)	100.0%

Sample

1st row	laura@northwindtraders.com
2nd row	steven@northwindtraders.com
3rd row	robert@northwindtraders.com
4th row	nancy@northwindtraders.com
5th row	michael@northwindtraders.com

Value	Count	Frequency (%)
laura@northwindtraders.com	1	11.1%
steven@northwindtraders.com	1	11.1%
robert@northwindtraders.com	1	11.1%
nancy@northwindtraders.com	1	11.1%
michael@northwindtraders.com	1	11.1%
jan@northwindtraders.com	1	11.1%
mariya@northwindtraders.com	1	11.1%
andrew@northwindtraders.com	1	11.1%
anne@northwindtraders.com	1	11.1%

Most occurring characters

Value	Count	Frequency (%)
r	32	13.5%
n	25	10.5%
t	20	8.4%
d	19	8.0%
o	19	8.0%
a	18	7.6%
e	15	6.3%
c	11	4.6%
i	11	4.6%
m	11	4.6%
Other values (11)	56	23.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	237	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
r	32	13.5%
n	25	10.5%
t	20	8.4%
d	19	8.0%
o	19	8.0%
a	18	7.6%
e	15	6.3%
c	11	4.6%
i	11	4.6%
m	11	4.6%
Other values (11)	56	23.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	237	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
r	32	13.5%
n	25	10.5%
t	20	8.4%
d	19	8.0%
o	19	8.0%
a	18	7.6%
e	15	6.3%
c	11	4.6%
i	11	4.6%
m	11	4.6%
Other values (11)	56	23.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	237	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
r	32	13.5%
n	25	10.5%
t	20	8.4%
d	19	8.0%
o	19	8.0%
a	18	7.6%
e	15	6.3%
c	11	4.6%
i	11	4.6%
m	11	4.6%
Other values (11)	56	23.6%

job_title
Categorical

High correlation Missing

Distinct	12
Distinct (%)	24.5%
Missing	463
Missing (%)	90.4%
Memory size	29.0 KiB

Purchasing Manager	13
Sales Representative	8
Owner	7
Sales Manager	6
Purchasing Representative	6
Other values (7)	9

Length

Max length	25
Median length	21
Mean length	16.857143
Min length	5

Characters and Unicode

Total characters	826
Distinct characters	28
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	10.2%

Sample

1st row	Sales Coordinator
2nd row	Sales Manager
3rd row	Sales Representative
4th row	Sales Representative
5th row	Sales Representative

Common Values

Value	Count	Frequency (%)
Purchasing Manager	13	2.5%
Sales Representative	8	1.6%
Owner	7	1.4%
Sales Manager	6	1.2%
Purchasing Representative	6	1.2%
Marketing Manager	2	0.4%
Accounting Assistant	2	0.4%
Sales Coordinator	1	0.2%
Vice President, Sales	1	0.2%
Marketing Assistant	1	0.2%
Other values (2)	2	0.4%
(Missing)	463	90.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
manager	22	23.9%
purchasing	20	21.7%
sales	16	17.4%
representative	14	15.2%
owner	7	7.6%
assistant	4	4.3%
marketing	3	3.3%
accounting	3	3.3%
coordinator	1	1.1%
vice	1	1.1%

Most occurring characters

Value	Count	Frequency (%)
e	107	13.0%
a	102	12.3%
n	78	9.4%
r	69	8.4%
s	63	7.6%
g	48	5.8%
i	47	5.7%
t	44	5.3%
	43	5.2%
c	27	3.3%
Other values (18)	198	24.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	826	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	107	13.0%
a	102	12.3%
n	78	9.4%
r	69	8.4%
s	63	7.6%
g	48	5.8%
i	47	5.7%
t	44	5.3%
	43	5.2%
c	27	3.3%
Other values (18)	198	24.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	826	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	107	13.0%
a	102	12.3%
n	78	9.4%
r	69	8.4%
s	63	7.6%
g	48	5.8%
i	47	5.7%
t	44	5.3%
	43	5.2%
c	27	3.3%
Other values (18)	198	24.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	826	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	107	13.0%
a	102	12.3%
n	78	9.4%
r	69	8.4%
s	63	7.6%
g	48	5.8%
i	47	5.7%
t	44	5.3%
	43	5.2%
c	27	3.3%
Other values (18)	198	24.0%

business_phone
Categorical

Constant Missing

Distinct	1
Distinct (%)	2.6%
Missing	473
Missing (%)	92.4%
Memory size	28.7 KiB

(123)555-0100	39

Length

Max length	13
Median length	13
Mean length	13
Min length	13

Characters and Unicode

Total characters	507
Distinct characters	8
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	(123)555-0100
2nd row	(123)555-0100
3rd row	(123)555-0100
4th row	(123)555-0100
5th row	(123)555-0100

Common Values

Value	Count	Frequency (%)
(123)555-0100	39	7.6%
(Missing)	473	92.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
123)555-0100	39	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	117	23.1%
5	117	23.1%
1	78	15.4%
(	39	7.7%
3	39	7.7%
2	39	7.7%
)	39	7.7%
-	39	7.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	507	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	117	23.1%
5	117	23.1%
1	78	15.4%
(	39	7.7%
3	39	7.7%
2	39	7.7%
)	39	7.7%
-	39	7.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	507	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	117	23.1%
5	117	23.1%
1	78	15.4%
(	39	7.7%
3	39	7.7%
2	39	7.7%
)	39	7.7%
-	39	7.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	507	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	117	23.1%
5	117	23.1%
1	78	15.4%
(	39	7.7%
3	39	7.7%
2	39	7.7%
)	39	7.7%
-	39	7.7%

home_phone
Categorical

Constant Missing

Distinct	1
Distinct (%)	11.1%
Missing	503
Missing (%)	98.2%
Memory size	28.2 KiB

(123)555-0102	9

Length

Max length	13
Median length	13
Mean length	13
Min length	13

Characters and Unicode

Total characters	117
Distinct characters	8
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	(123)555-0102
2nd row	(123)555-0102
3rd row	(123)555-0102
4th row	(123)555-0102
5th row	(123)555-0102

Common Values

Value	Count	Frequency (%)
(123)555-0102	9	1.8%
(Missing)	503	98.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
123)555-0102	9	100.0%

Most occurring characters

Value	Count	Frequency (%)
5	27	23.1%
1	18	15.4%
0	18	15.4%
2	18	15.4%
3	9	7.7%
(	9	7.7%
)	9	7.7%
-	9	7.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	117	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
5	27	23.1%
1	18	15.4%
0	18	15.4%
2	18	15.4%
3	9	7.7%
(	9	7.7%
)	9	7.7%
-	9	7.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	117	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
5	27	23.1%
1	18	15.4%
0	18	15.4%
2	18	15.4%
3	9	7.7%
(	9	7.7%
)	9	7.7%
-	9	7.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	117	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
5	27	23.1%
1	18	15.4%
0	18	15.4%
2	18	15.4%
3	9	7.7%
(	9	7.7%
)	9	7.7%
-	9	7.7%

mobile_phone
Unsupported

Missing Rejected Unsupported

Missing	512
Missing (%)	100.0%
Memory size	4.1 KiB

fax_number
Categorical

High correlation Missing

Distinct	2
Distinct (%)	5.1%
Missing	473
Missing (%)	92.4%
Memory size	28.7 KiB

(123)555-0101	30
(123)555-0103	9

Length

Max length	13
Median length	13
Mean length	13
Min length	13

Characters and Unicode

Total characters	507
Distinct characters	8
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	(123)555-0103
2nd row	(123)555-0103
3rd row	(123)555-0103
4th row	(123)555-0103
5th row	(123)555-0103

Common Values

Value	Count	Frequency (%)
(123)555-0101	30	5.9%
(123)555-0103	9	1.8%
(Missing)	473	92.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
123)555-0101	30	76.9%
123)555-0103	9	23.1%

Most occurring characters

Value	Count	Frequency (%)
5	117	23.1%
1	108	21.3%
0	78	15.4%
3	48	9.5%
2	39	7.7%
(	39	7.7%
)	39	7.7%
-	39	7.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	507	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
5	117	23.1%
1	108	21.3%
0	78	15.4%
3	48	9.5%
2	39	7.7%
(	39	7.7%
)	39	7.7%
-	39	7.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	507	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
5	117	23.1%
1	108	21.3%
0	78	15.4%
3	48	9.5%
2	39	7.7%
(	39	7.7%
)	39	7.7%
-	39	7.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	507	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
5	117	23.1%
1	108	21.3%
0	78	15.4%
3	48	9.5%
2	39	7.7%
(	39	7.7%
)	39	7.7%
-	39	7.7%

address
Text

Missing

Distinct	39
Distinct (%)	92.9%
Missing	470
Missing (%)	91.8%
Memory size	17.7 KiB

Length

Max length	15
Median length	14
Mean length	14.47619
Min length	14

Characters and Unicode

Total characters	608
Distinct characters	23
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	37 ?
Unique (%)	88.1%

Sample

1st row	123 8th Avenue
2nd row	123 5th Avenue
3rd row	123 7th Avenue
4th row	123 1st Avenue
5th row	123 6th Avenue

Value	Count	Frequency (%)
street	33	26.2%
123	25	19.8%
789	11	8.7%
avenue	9	7.1%
456	6	4.8%
any	3	2.4%
1st	3	2.4%
5th	2	1.6%
7th	2	1.6%
8th	2	1.6%
Other values (25)	30	23.8%

Most occurring characters

Value	Count	Frequency (%)
t	101	16.6%
e	84	13.8%
	84	13.8%
1	40	6.6%
2	39	6.4%
r	35	5.8%
S	33	5.4%
h	32	5.3%
3	29	4.8%
9	15	2.5%
Other values (13)	116	19.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	608	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
t	101	16.6%
e	84	13.8%
	84	13.8%
1	40	6.6%
2	39	6.4%
r	35	5.8%
S	33	5.4%
h	32	5.3%
3	29	4.8%
9	15	2.5%
Other values (13)	116	19.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	608	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
t	101	16.6%
e	84	13.8%
	84	13.8%
1	40	6.6%
2	39	6.4%
r	35	5.8%
S	33	5.4%
h	32	5.3%
3	29	4.8%
9	15	2.5%
Other values (13)	116	19.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	608	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
t	101	16.6%
e	84	13.8%
	84	13.8%
1	40	6.6%
2	39	6.4%
r	35	5.8%
S	33	5.4%
h	32	5.3%
3	29	4.8%
9	15	2.5%
Other values (13)	116	19.1%

city
Categorical

High correlation Missing

Distinct	19
Distinct (%)	45.2%
Missing	470
Missing (%)	91.8%
Memory size	28.5 KiB

Seattle	7
Memphis	5
Redmond	3
New York	2
Los Angelas	2
Other values (14)	23

Length

Max length	14
Median length	13
Mean length	7.9761905
Min length	5

Characters and Unicode

Total characters	335
Distinct characters	36
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	11.9%

Sample

1st row	Redmond
2nd row	Seattle
3rd row	Seattle
4th row	Seattle
5th row	Redmond

Common Values

Value	Count	Frequency (%)
Seattle	7	1.4%
Memphis	5	1.0%
Redmond	3	0.6%
New York	2	0.4%
Los Angelas	2	0.4%
Miami	2	0.4%
Denver	2	0.4%
Las Vegas	2	0.4%
Minneapolis	2	0.4%
Boston	2	0.4%
Other values (9)	13	2.5%
(Missing)	470	91.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
seattle	7	13.2%
memphis	5	9.4%
redmond	3	5.7%
new	2	3.8%
york	2	3.8%
los	2	3.8%
angelas	2	3.8%
miami	2	3.8%
denver	2	3.8%
las	2	3.8%
Other values (15)	24	45.3%

Most occurring characters

Value	Count	Frequency (%)
e	44	13.1%
a	30	9.0%
t	22	6.6%
l	22	6.6%
i	22	6.6%
o	21	6.3%
n	19	5.7%
s	19	5.7%
M	11	3.3%
	11	3.3%
Other values (26)	114	34.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	335	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	44	13.1%
a	30	9.0%
t	22	6.6%
l	22	6.6%
i	22	6.6%
o	21	6.3%
n	19	5.7%
s	19	5.7%
M	11	3.3%
	11	3.3%
Other values (26)	114	34.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	335	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	44	13.1%
a	30	9.0%
t	22	6.6%
l	22	6.6%
i	22	6.6%
o	21	6.3%
n	19	5.7%
s	19	5.7%
M	11	3.3%
	11	3.3%
Other values (26)	114	34.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	335	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	44	13.1%
a	30	9.0%
t	22	6.6%
l	22	6.6%
i	22	6.6%
o	21	6.3%
n	19	5.7%
s	19	5.7%
M	11	3.3%
	11	3.3%
Other values (26)	114	34.0%

state_province
Categorical

High correlation Missing

Distinct	15
Distinct (%)	35.7%
Missing	470
Missing (%)	91.8%
Memory size	28.2 KiB

WA	12
TN	5
CA	3
CO	2
FL	2
Other values (10)	18

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	84
Distinct characters	16
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	4.8%

Sample

1st row	WA
2nd row	WA
3rd row	WA
4th row	WA
5th row	WA

Common Values

Value	Count	Frequency (%)
WA	12	2.3%
TN	5	1.0%
CA	3	0.6%
CO	2	0.4%
FL	2	0.4%
MA	2	0.4%
IL	2	0.4%
NY	2	0.4%
OR	2	0.4%
MN	2	0.4%
Other values (5)	8	1.6%
(Missing)	470	91.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
wa	12	28.6%
tn	5	11.9%
ca	3	7.1%
co	2	4.8%
fl	2	4.8%
ma	2	4.8%
il	2	4.8%
ny	2	4.8%
or	2	4.8%
mn	2	4.8%
Other values (5)	8	19.0%

Most occurring characters

Value	Count	Frequency (%)
A	17	20.2%
W	14	16.7%
N	11	13.1%
T	7	8.3%
I	6	7.1%
C	5	6.0%
L	4	4.8%
O	4	4.8%
M	4	4.8%
F	2	2.4%
Other values (6)	10	11.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	84	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
A	17	20.2%
W	14	16.7%
N	11	13.1%
T	7	8.3%
I	6	7.1%
C	5	6.0%
L	4	4.8%
O	4	4.8%
M	4	4.8%
F	2	2.4%
Other values (6)	10	11.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	84	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
A	17	20.2%
W	14	16.7%
N	11	13.1%
T	7	8.3%
I	6	7.1%
C	5	6.0%
L	4	4.8%
O	4	4.8%
M	4	4.8%
F	2	2.4%
Other values (6)	10	11.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	84	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
A	17	20.2%
W	14	16.7%
N	11	13.1%
T	7	8.3%
I	6	7.1%
C	5	6.0%
L	4	4.8%
O	4	4.8%
M	4	4.8%
F	2	2.4%
Other values (6)	10	11.9%

zip_postal_code
Categorical

Constant Missing

Distinct	1
Distinct (%)	2.4%
Missing	470
Missing (%)	91.8%
Memory size	28.4 KiB

99999	42

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	210
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	99999
2nd row	99999
3rd row	99999
4th row	99999
5th row	99999

Common Values

Value	Count	Frequency (%)
99999	42	8.2%
(Missing)	470	91.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
99999	42	100.0%

Most occurring characters

Value	Count	Frequency (%)
9	210	100.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	210	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
9	210	100.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	210	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
9	210	100.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	210	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
9	210	100.0%

country_region
Categorical

Constant Missing

Distinct	1
Distinct (%)	2.4%
Missing	470
Missing (%)	91.8%
Memory size	28.3 KiB

USA	42

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	126
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	USA
2nd row	USA
3rd row	USA
4th row	USA
5th row	USA

Common Values

Value	Count	Frequency (%)
USA	42	8.2%
(Missing)	470	91.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
usa	42	100.0%

Most occurring characters

Value	Count	Frequency (%)
U	42	33.3%
S	42	33.3%
A	42	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	126	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
U	42	33.3%
S	42	33.3%
A	42	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	126	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
U	42	33.3%
S	42	33.3%
A	42	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	126	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
U	42	33.3%
S	42	33.3%
A	42	33.3%

web_page
Categorical

High correlation Missing

Distinct	2
Distinct (%)	22.2%
Missing	503
Missing (%)	98.2%
Memory size	28.6 KiB

http://northwindtraders.com#http://northwindtraders.com/#	8
#http://northwindtraders.com#	1

Length

Max length	57
Median length	57
Mean length	53.888889
Min length	29

Characters and Unicode

Total characters	485
Distinct characters	18
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	11.1%

Sample

1st row	http://northwindtraders.com#http://northwindtraders.com/#
2nd row	http://northwindtraders.com#http://northwindtraders.com/#
3rd row	http://northwindtraders.com#http://northwindtraders.com/#
4th row	#http://northwindtraders.com#
5th row	http://northwindtraders.com#http://northwindtraders.com/#

Common Values

Value	Count	Frequency (%)
http://northwindtraders.com#http://northwindtraders.com/#	8	1.6%
#http://northwindtraders.com#	1	0.2%
(Missing)	503	98.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
http://northwindtraders.com#http://northwindtraders.com	8	88.9%
http://northwindtraders.com	1	11.1%

Most occurring characters

Value	Count	Frequency (%)
t	68	14.0%
r	51	10.5%
/	42	8.7%
h	34	7.0%
o	34	7.0%
n	34	7.0%
d	34	7.0%
#	18	3.7%
p	17	3.5%
:	17	3.5%
Other values (8)	136	28.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	485	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
t	68	14.0%
r	51	10.5%
/	42	8.7%
h	34	7.0%
o	34	7.0%
n	34	7.0%
d	34	7.0%
#	18	3.7%
p	17	3.5%
:	17	3.5%
Other values (8)	136	28.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	485	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
t	68	14.0%
r	51	10.5%
/	42	8.7%
h	34	7.0%
o	34	7.0%
n	34	7.0%
d	34	7.0%
#	18	3.7%
p	17	3.5%
:	17	3.5%
Other values (8)	136	28.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	485	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
t	68	14.0%
r	51	10.5%
/	42	8.7%
h	34	7.0%
o	34	7.0%
n	34	7.0%
d	34	7.0%
#	18	3.7%
p	17	3.5%
:	17	3.5%
Other values (8)	136	28.0%

notes
Text

Missing

Distinct	20
Distinct (%)	90.9%
Missing	490
Missing (%)	95.7%
Memory size	17.6 KiB

Length

Max length	119
Median length	37
Mean length	45.772727
Min length	24

Characters and Unicode

Total characters	1007
Distinct characters	43
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	18 ?
Unique (%)	81.8%

Sample

1st row	Reads and writes French.
2nd row	Joined the company as a sales representative and was promoted to sales manager. Fluent in French.
3rd row	Fluent in Japanese and can read and write French, Portuguese, and Spanish.
4th row	Was hired as a sales associate and was promoted to sales representative.
5th row	Joined the company as a sales representative, was promoted to sales manager and was then named vice president of sales.

Value	Count	Frequency (%)
purchase	16	9.7%
generated	16	9.7%
based	16	9.7%
on	16	9.7%
order	16	9.7%
and	8	4.8%
sales	7	4.2%
was	5	3.0%
french	4	2.4%
a	3	1.8%
Other values (40)	58	35.2%

Most occurring characters

Value	Count	Frequency (%)
e	147	14.6%
	144	14.3%
a	93	9.2%
r	86	8.5%
n	66	6.6%
d	66	6.6%
s	65	6.5%
t	39	3.9%
o	32	3.2%
c	25	2.5%
Other values (33)	244	24.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1007	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	147	14.6%
	144	14.3%
a	93	9.2%
r	86	8.5%
n	66	6.6%
d	66	6.6%
s	65	6.5%
t	39	3.9%
o	32	3.2%
c	25	2.5%
Other values (33)	244	24.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1007	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	147	14.6%
	144	14.3%
a	93	9.2%
r	86	8.5%
n	66	6.6%
d	66	6.6%
s	65	6.5%
t	39	3.9%
o	32	3.2%
c	25	2.5%
Other values (33)	244	24.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1007	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	147	14.6%
	144	14.3%
a	93	9.2%
r	86	8.5%
n	66	6.6%
d	66	6.6%
s	65	6.5%
t	39	3.9%
o	32	3.2%
c	25	2.5%
Other values (33)	244	24.2%

attachments
Categorical

Constant Missing

Distinct	1
Distinct (%)	1.0%
Missing	415
Missing (%)	81.1%
Memory size	28.2 KiB

	97

Length

Max length	0
Median length	0
Mean length	0
Min length	0

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

Value	Count	Frequency (%)
	97	18.9%
(Missing)	415	81.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

type_name
Text

Missing

Distinct	4
Distinct (%)	100.0%
Missing	508
Missing (%)	99.2%
Memory size	16.2 KiB

Length

Max length	9
Median length	6
Mean length	6.25
Min length	4

Characters and Unicode

Total characters	25
Distinct characters	18
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	100.0%

Sample

1st row	Purchased
2nd row	Sold
3rd row	On Hold
4th row	Waste

Value	Count	Frequency (%)
purchased	1	20.0%
sold	1	20.0%
on	1	20.0%
hold	1	20.0%
waste	1	20.0%

Most occurring characters

Value	Count	Frequency (%)
d	3	12.0%
a	2	8.0%
l	2	8.0%
o	2	8.0%
s	2	8.0%
e	2	8.0%
u	1	4.0%
P	1	4.0%
h	1	4.0%
c	1	4.0%
Other values (8)	8	32.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	25	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
d	3	12.0%
a	2	8.0%
l	2	8.0%
o	2	8.0%
s	2	8.0%
e	2	8.0%
u	1	4.0%
P	1	4.0%
h	1	4.0%
c	1	4.0%
Other values (8)	8	32.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	25	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
d	3	12.0%
a	2	8.0%
l	2	8.0%
o	2	8.0%
s	2	8.0%
e	2	8.0%
u	1	4.0%
P	1	4.0%
h	1	4.0%
c	1	4.0%
Other values (8)	8	32.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	25	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
d	3	12.0%
a	2	8.0%
l	2	8.0%
o	2	8.0%
s	2	8.0%
e	2	8.0%
u	1	4.0%
P	1	4.0%
h	1	4.0%
c	1	4.0%
Other values (8)	8	32.0%

transaction_type
Categorical

High correlation Missing

Distinct	3
Distinct (%)	2.9%
Missing	410
Missing (%)	80.1%
Memory size	28.3 KiB

2	49
1	43
3	10

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	102
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
2	49	9.6%
1	43	8.4%
3	10	2.0%
(Missing)	410	80.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2	49	48.0%
1	43	42.2%
3	10	9.8%

Most occurring characters

Value	Count	Frequency (%)
2	49	48.0%
1	43	42.2%
3	10	9.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	102	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
2	49	48.0%
1	43	42.2%
3	10	9.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	102	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
2	49	48.0%
1	43	42.2%
3	10	9.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	102	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
2	49	48.0%
1	43	42.2%
3	10	9.8%

transaction_created_date
Date

Missing

Distinct	102
Distinct (%)	100.0%
Missing	410
Missing (%)	80.1%
Memory size	4.1 KiB

Minimum	2006-03-22 16:02:28
Maximum	2006-04-25 17:04:05
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

transaction_modified_date
Date

Missing

Distinct	88
Distinct (%)	86.3%
Missing	410
Missing (%)	80.1%
Memory size	4.1 KiB

Minimum	2006-03-22 16:02:28
Maximum	2006-04-25 17:04:57
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

product_id
Real number (ℝ)

Missing

Distinct	29
Distinct (%)	13.5%
Missing	297
Missing (%)	58.0%
Infinite	0
Infinite (%)	0.0%
Mean	37.637209

Minimum	1
Maximum	85
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	17
median	41
Q3	52
95-th percentile	81
Maximum	85
Range	84
Interquartile range (IQR)	35

Descriptive statistics

Standard deviation	25.108708
Coefficient of variation (CV)	0.66712459
Kurtosis	-1.0386113
Mean	37.637209
Median Absolute Deviation (MAD)	22
Skewness	0.21449306
Sum	8092
Variance	630.44721
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
19	17	3.3%
34	17	3.3%
43	17	3.3%
48	14	2.7%
41	14	2.7%
8	12	2.3%
81	11	2.1%
80	10	2.0%
40	9	1.8%
72	9	1.8%
Other values (19)	85	16.6%
(Missing)	297	58.0%

Value	Count	Frequency (%)
1	8	1.6%
3	5	1.0%
4	7	1.4%
5	4	0.8%
6	7	1.4%
7	6	1.2%
8	12	2.3%
14	2	0.4%
17	4	0.8%
19	17	3.3%

Value	Count	Frequency (%)
85	1	0.2%
81	11	2.1%
80	10	2.0%
77	2	0.4%
74	4	0.8%
72	9	1.8%
66	2	0.4%
65	2	0.4%
57	6	1.2%
56	5	1.0%

quantity
Real number (ℝ)

Missing

Distinct	25
Distinct (%)	11.6%
Missing	297
Missing (%)	58.0%
Infinite	0
Infinite (%)	0.0%
Mean	64.269767

Minimum	0
Maximum	300
Zeros	2
Zeros (%)	0.4%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	0
5-th percentile	10
Q1	20
median	40
Q3	87
95-th percentile	265
Maximum	300
Range	300
Interquartile range (IQR)	67

Descriptive statistics

Standard deviation	72.093214
Coefficient of variation (CV)	1.1217283
Kurtosis	4.0195746
Mean	64.269767
Median Absolute Deviation (MAD)	20
Skewness	2.1260061
Sum	13818
Variance	5197.4316
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=25)

Value	Count	Frequency (%)
40.0	43	8.4%
10.0	24	4.7%
100.0	22	4.3%
20.0	19	3.7%
50.0	17	3.3%
25.0	16	3.1%
30.0	16	3.1%
300.0	11	2.1%
200.0	8	1.6%
120.0	5	1.0%
Other values (15)	34	6.6%
(Missing)	297	58.0%

Value	Count	Frequency (%)
0.0	2	0.4%
1.0	2	0.4%
3.0	2	0.4%
5.0	2	0.4%
10.0	24	4.7%
12.0	1	0.2%
15.0	4	0.8%
17.0	2	0.4%
20.0	19	3.7%
25.0	16	3.1%

Value	Count	Frequency (%)
300.0	11	2.1%
250.0	2	0.4%
200.0	8	1.6%
125.0	2	0.4%
120.0	5	1.0%
110.0	1	0.2%
100.0	22	4.3%
90.0	2	0.4%
87.0	2	0.4%
80.0	4	0.8%

purchase_order_id
Real number (ℝ)

High correlation Missing

Distinct	28
Distinct (%)	40.0%
Missing	442
Missing (%)	86.3%
Infinite	0
Infinite (%)	0.0%
Mean	102.1

Minimum	90
Maximum	148
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	90
5-th percentile	90
Q1	92
median	97
Q3	105.75
95-th percentile	144.2
Maximum	148
Range	58
Interquartile range (IQR)	13.75

Descriptive statistics

Standard deviation	15.55183
Coefficient of variation (CV)	0.15231959
Kurtosis	3.1476644
Mean	102.1
Median Absolute Deviation (MAD)	6
Skewness	1.977922
Sum	7147
Variance	241.85942
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=28)

Value	Count	Frequency (%)
92	15	2.9%
91	7	1.4%
90	5	1.0%
93	3	0.6%
104	2	0.4%
100	2	0.4%
111	2	0.4%
101	2	0.4%
97	2	0.4%
103	2	0.4%
Other values (18)	28	5.5%
(Missing)	442	86.3%

Value	Count	Frequency (%)
90	5	1.0%
91	7	1.4%
92	15	2.9%
93	3	0.6%
94	1	0.2%
95	1	0.2%
96	2	0.4%
97	2	0.4%
98	2	0.4%
99	2	0.4%

Value	Count	Frequency (%)
148	1	0.2%
147	1	0.2%
146	2	0.4%
142	1	0.2%
141	1	0.2%
140	1	0.2%
111	2	0.4%
110	1	0.2%
109	2	0.4%
108	2	0.4%

customer_order_id
Unsupported

Missing Rejected Unsupported

Missing	512
Missing (%)	100.0%
Memory size	4.6 KiB

comments
Text

Missing

Distinct	12
Distinct (%)	85.7%
Missing	498
Missing (%)	97.3%
Memory size	17.0 KiB

Length

Max length	36
Median length	36
Mean length	36
Min length	36

Characters and Unicode

Total characters	504
Distinct characters	28
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	10 ?
Unique (%)	71.4%

Sample

1st row	Fill Back Ordered product, Order #42
2nd row	Fill Back Ordered product, Order #48
3rd row	Fill Back Ordered product, Order #48
4th row	Fill Back Ordered product, Order #33
5th row	Fill Back Ordered product, Order #46

Value	Count	Frequency (%)
fill	14	16.7%
back	14	16.7%
ordered	14	16.7%
product	14	16.7%
order	14	16.7%
48	2	2.4%
46	2	2.4%
42	1	1.2%
33	1	1.2%
45	1	1.2%
Other values (7)	7	8.3%

Most occurring characters

Value	Count	Frequency (%)
	70	13.9%
r	70	13.9%
d	56	11.1%
e	42	8.3%
O	28	5.6%
c	28	5.6%
l	28	5.6%
i	14	2.8%
F	14	2.8%
k	14	2.8%
Other values (18)	140	27.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	504	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	70	13.9%
r	70	13.9%
d	56	11.1%
e	42	8.3%
O	28	5.6%
c	28	5.6%
l	28	5.6%
i	14	2.8%
F	14	2.8%
k	14	2.8%
Other values (18)	140	27.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	504	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	70	13.9%
r	70	13.9%
d	56	11.1%
e	42	8.3%
O	28	5.6%
c	28	5.6%
l	28	5.6%
i	14	2.8%
F	14	2.8%
k	14	2.8%
Other values (18)	140	27.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	504	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	70	13.9%
r	70	13.9%
d	56	11.1%
e	42	8.3%
O	28	5.6%
c	28	5.6%
l	28	5.6%
i	14	2.8%
F	14	2.8%
k	14	2.8%
Other values (18)	140	27.8%

order_id
Real number (ℝ)

High correlation Missing

Distinct	40
Distinct (%)	43.0%
Missing	419
Missing (%)	81.8%
Infinite	0
Infinite (%)	0.0%
Mean	52.946237

Minimum	30
Maximum	81
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	30
5-th percentile	31
Q1	39
median	48
Q3	70
95-th percentile	79
Maximum	81
Range	51
Interquartile range (IQR)	31

Descriptive statistics

Standard deviation	16.37294
Coefficient of variation (CV)	0.30923709
Kurtosis	-1.3167916
Mean	52.946237
Median Absolute Deviation (MAD)	13
Skewness	0.29043732
Sum	4924
Variance	268.07317
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=40)

Value	Count	Frequency (%)
51	4	0.8%
31	4	0.8%
42	4	0.8%
32	3	0.6%
30	3	0.6%
46	3	0.6%
79	3	0.6%
63	3	0.6%
58	3	0.6%
44	3	0.6%
Other values (30)	60	11.7%
(Missing)	419	81.8%

Value	Count	Frequency (%)
30	3	0.6%
31	4	0.8%
32	3	0.6%
33	2	0.4%
34	2	0.4%
35	2	0.4%
36	2	0.4%
37	2	0.4%
38	2	0.4%
39	2	0.4%

Value	Count	Frequency (%)
81	2	0.4%
80	1	0.2%
79	3	0.6%
78	2	0.4%
77	2	0.4%
76	2	0.4%
75	2	0.4%
74	2	0.4%
73	2	0.4%
72	2	0.4%

invoice_date
Date

Missing

Distinct	35
Distinct (%)	100.0%
Missing	477
Missing (%)	93.2%
Memory size	4.1 KiB

Minimum	2006-03-22 16:08:59
Maximum	2006-04-04 11:43:08
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=35)

due_date
Unsupported

Missing Rejected Unsupported

Missing	512
Missing (%)	100.0%
Memory size	4.1 KiB

tax
Categorical

Constant Missing

Distinct	1
Distinct (%)	2.9%
Missing	477
Missing (%)	93.2%
Memory size	28.3 KiB

0.0	35

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	105
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	35	6.8%
(Missing)	477	93.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0.0	35	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	70	66.7%
.	35	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	105	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	70	66.7%
.	35	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	105	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	70	66.7%
.	35	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	105	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	70	66.7%
.	35	33.3%

shipping
Categorical

Constant Missing

Distinct	1
Distinct (%)	2.9%
Missing	477
Missing (%)	93.2%
Memory size	28.3 KiB

0.0	35

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	105
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	35	6.8%
(Missing)	477	93.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0.0	35	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	70	66.7%
.	35	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	105	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	70	66.7%
.	35	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	105	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	70	66.7%
.	35	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	105	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	70	66.7%
.	35	33.3%

amount_due
Categorical

Constant Missing

Distinct	1
Distinct (%)	2.9%
Missing	477
Missing (%)	93.2%
Memory size	28.3 KiB

0.0	35

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	105
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	35	6.8%
(Missing)	477	93.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0.0	35	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	70	66.7%
.	35	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	105	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	70	66.7%
.	35	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	105	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	70	66.7%
.	35	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	105	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	70	66.7%
.	35	33.3%

unit_price
Real number (ℝ)

High correlation Missing

Distinct	22
Distinct (%)	37.9%
Missing	454
Missing (%)	88.7%
Infinite	0
Infinite (%)	0.0%
Mean	22.271724

Minimum	2.99
Maximum	81
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.1 KiB

Quantile statistics

Minimum	2.99
5-th percentile	2.99
Q1	9.65
median	18
Q3	37.2
95-th percentile	47.05
Maximum	81
Range	78.01
Interquartile range (IQR)	27.55

Descriptive statistics

Standard deviation	16.902057
Coefficient of variation (CV)	0.75890204
Kurtosis	0.98226676
Mean	22.271724
Median Absolute Deviation (MAD)	8.8
Skewness	1.0515845
Sum	1291.76
Variance	285.67953
Monotonicity	Increasing

Histogram with fixed size bins (bins=22)

Value	Count	Frequency (%)
46	5	1.0%
12.75	5	1.0%
9.2	4	0.8%
9.65	4	0.8%
2.99	4	0.8%
3.5	4	0.8%
40	4	0.8%
10	3	0.6%
18.4	3	0.6%
14	3	0.6%
Other values (12)	19	3.7%
(Missing)	454	88.7%

Value	Count	Frequency (%)
2.99	4	0.8%
3.5	4	0.8%
7	1	0.2%
9.2	4	0.8%
9.65	4	0.8%
10	3	0.6%
12.75	5	1.0%
14	3	0.6%
18	2	0.4%
18.4	3	0.6%

Value	Count	Frequency (%)
81	1	0.2%
53	2	0.4%
46	5	1.0%
40	4	0.8%
39	1	0.2%
38	2	0.4%
34.8	2	0.4%
30	2	0.4%
25	2	0.4%
22	2	0.4%

discount
Categorical

Constant Missing

Distinct	1
Distinct (%)	1.7%
Missing	454
Missing (%)	88.7%
Memory size	28.4 KiB

0.0	58

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	174
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	58	11.3%
(Missing)	454	88.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0.0	58	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	116	66.7%
.	58	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	174	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	116	66.7%
.	58	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	174	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	116	66.7%
.	58	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	174	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	116	66.7%
.	58	33.3%

status_id
Categorical

High correlation Missing

Distinct	5
Distinct (%)	3.7%
Missing	378
Missing (%)	73.8%
Memory size	28.4 KiB

2	75
3	31
0	17
1	10
5	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	134
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.7%

Sample

1st row	2
2nd row	1
3rd row	1
4th row	5
5th row	2

Common Values

Value	Count	Frequency (%)
2	75	14.6%
3	31	6.1%
0	17	3.3%
1	10	2.0%
5	1	0.2%
(Missing)	378	73.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2	75	56.0%
3	31	23.1%
0	17	12.7%
1	10	7.5%
5	1	0.7%

Most occurring characters

Value	Count	Frequency (%)
2	75	56.0%
3	31	23.1%
0	17	12.7%
1	10	7.5%
5	1	0.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	134	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
2	75	56.0%
3	31	23.1%
0	17	12.7%
1	10	7.5%
5	1	0.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	134	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
2	75	56.0%
3	31	23.1%
0	17	12.7%
1	10	7.5%
5	1	0.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	134	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
2	75	56.0%
3	31	23.1%
0	17	12.7%
1	10	7.5%
5	1	0.7%

date_allocated
Unsupported

Missing Rejected Unsupported

Missing	512
Missing (%)	100.0%
Memory size	4.1 KiB

inventory_id
Real number (ℝ)

High correlation Missing

Distinct	99
Distinct (%)	100.0%
Missing	413
Missing (%)	80.7%
Infinite	0
Infinite (%)	0.0%
Mean	85.151515

Minimum	35
Maximum	136
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	35
5-th percentile	39.9
Q1	59.5
median	84
Q3	111.5
95-th percentile	131.1
Maximum	136
Range	101
Interquartile range (IQR)	52

Descriptive statistics

Standard deviation	29.968474
Coefficient of variation (CV)	0.35194294
Kurtosis	-1.238445
Mean	85.151515
Median Absolute Deviation (MAD)	26
Skewness	0.033813886
Sum	8430
Variance	898.10946
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
73	1	0.2%
90	1	0.2%
87	1	0.2%
66	1	0.2%
86	1	0.2%
129	1	0.2%
135	1	0.2%
81	1	0.2%
69	1	0.2%
110	1	0.2%
Other values (89)	89	17.4%
(Missing)	413	80.7%

Value	Count	Frequency (%)
35	1	0.2%
36	1	0.2%
37	1	0.2%
38	1	0.2%
39	1	0.2%
40	1	0.2%
41	1	0.2%
42	1	0.2%
43	1	0.2%
44	1	0.2%

Value	Count	Frequency (%)
136	1	0.2%
135	1	0.2%
134	1	0.2%
133	1	0.2%
132	1	0.2%
131	1	0.2%
130	1	0.2%
129	1	0.2%
128	1	0.2%
127	1	0.2%

status
Text

Missing

Distinct	10
Distinct (%)	100.0%
Missing	502
Missing (%)	98.0%
Memory size	16.4 KiB

Length

Max length	9
Median length	8
Mean length	7
Min length	3

Characters and Unicode

Total characters	70
Distinct characters	26
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	10 ?
Unique (%)	100.0%

Sample

1st row	None
2nd row	Allocated
3rd row	Invoiced
4th row	Shipped
5th row	On Order

Value	Count	Frequency (%)
none	1	8.3%
allocated	1	8.3%
invoiced	1	8.3%
shipped	1	8.3%
on	1	8.3%
order	1	8.3%
no	1	8.3%
stock	1	8.3%
new	1	8.3%
submitted	1	8.3%
Other values (2)	2	16.7%

Most occurring characters

Value	Count	Frequency (%)
e	9	12.9%
o	7	10.0%
d	7	10.0%
t	4	5.7%
p	4	5.7%
N	3	4.3%
c	3	4.3%
l	3	4.3%
S	3	4.3%
n	3	4.3%
Other values (16)	24	34.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	70	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	9	12.9%
o	7	10.0%
d	7	10.0%
t	4	5.7%
p	4	5.7%
N	3	4.3%
c	3	4.3%
l	3	4.3%
S	3	4.3%
n	3	4.3%
Other values (16)	24	34.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	70	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	9	12.9%
o	7	10.0%
d	7	10.0%
t	4	5.7%
p	4	5.7%
N	3	4.3%
c	3	4.3%
l	3	4.3%
S	3	4.3%
n	3	4.3%
Other values (16)	24	34.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	70	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	9	12.9%
o	7	10.0%
d	7	10.0%
t	4	5.7%
p	4	5.7%
N	3	4.3%
c	3	4.3%
l	3	4.3%
S	3	4.3%
n	3	4.3%
Other values (16)	24	34.3%

customer_id
Real number (ℝ)

High correlation Missing

Distinct	15
Distinct (%)	31.2%
Missing	464
Missing (%)	90.6%
Infinite	0
Infinite (%)	0.0%
Mean	12.854167

Minimum	1
Maximum	29
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	6
median	8.5
Q3	25.25
95-th percentile	29
Maximum	29
Range	28
Interquartile range (IQR)	19.25

Descriptive statistics

Standard deviation	9.8152933
Coefficient of variation (CV)	0.76358846
Kurtosis	-1.1598277
Mean	12.854167
Median Absolute Deviation (MAD)	4
Skewness	0.74212086
Sum	617
Variance	96.339982
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=15)

Value	Count	Frequency (%)
8	6	1.2%
6	6	1.2%
4	5	1.0%
10	4	0.8%
29	4	0.8%
28	4	0.8%
3	3	0.6%
25	2	0.4%
1	2	0.4%
27	2	0.4%
Other values (5)	10	2.0%
(Missing)	464	90.6%

Value	Count	Frequency (%)
1	2	0.4%
3	3	0.6%
4	5	1.0%
6	6	1.2%
7	2	0.4%
8	6	1.2%
9	2	0.4%
10	4	0.8%
11	2	0.4%
12	2	0.4%

Value	Count	Frequency (%)
29	4	0.8%
28	4	0.8%
27	2	0.4%
26	2	0.4%
25	2	0.4%
12	2	0.4%
11	2	0.4%
10	4	0.8%
9	2	0.4%
8	6	1.2%

order_date
Date

Missing

Distinct	28
Distinct (%)	58.3%
Missing	464
Missing (%)	90.6%
Memory size	4.1 KiB

Minimum	2006-01-15 00:00:00
Maximum	2006-06-23 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=28)

shipped_date
Date

Missing

Distinct	23
Distinct (%)	59.0%
Missing	473
Missing (%)	92.4%
Memory size	4.1 KiB

Minimum	2006-01-22 00:00:00
Maximum	2006-06-23 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=23)

shipper_id
Categorical

High correlation Missing

Distinct	3
Distinct (%)	7.0%
Missing	469
Missing (%)	91.6%
Memory size	28.2 KiB

2	18
3	17
1	8

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	43
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	2
3rd row	1
4th row	3
5th row	3

Common Values

Value	Count	Frequency (%)
2	18	3.5%
3	17	3.3%
1	8	1.6%
(Missing)	469	91.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2	18	41.9%
3	17	39.5%
1	8	18.6%

Most occurring characters

Value	Count	Frequency (%)
2	18	41.9%
3	17	39.5%
1	8	18.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	43	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
2	18	41.9%
3	17	39.5%
1	8	18.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	43	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
2	18	41.9%
3	17	39.5%
1	8	18.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	43	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
2	18	41.9%
3	17	39.5%
1	8	18.6%

ship_name
Categorical

High correlation Missing

Distinct	15
Distinct (%)	31.2%
Missing	464
Missing (%)	90.6%
Memory size	29.1 KiB

Elizabeth Andersen	6
Francisco Pérez-Olaeta	6
Christina Lee	5
Amritansh Raghav	4
Roland Wacker	4
Other values (10)	23

Length

Max length	22
Median length	16
Mean length	14.208333
Min length	7

Characters and Unicode

Total characters	682
Distinct characters	41
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	John Edwards
2nd row	Karen Toh
3rd row	Christina Lee
4th row	Christina Lee
5th row	Elizabeth Andersen

Common Values

Value	Count	Frequency (%)
Elizabeth Andersen	6	1.2%
Francisco Pérez-Olaeta	6	1.2%
Christina Lee	5	1.0%
Amritansh Raghav	4	0.8%
Roland Wacker	4	0.8%
Soo Jung Lee	4	0.8%
Thomas Axen	3	0.6%
Anna Bedecs	2	0.4%
Karen Toh	2	0.4%
John Edwards	2	0.4%
Other values (5)	10	2.0%
(Missing)	464	90.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
lee	9	9.0%
andersen	6	6.0%
francisco	6	6.0%
pérez-olaeta	6	6.0%
elizabeth	6	6.0%
christina	5	5.0%
amritansh	4	4.0%
raghav	4	4.0%
roland	4	4.0%
wacker	4	4.0%
Other values (19)	46	46.0%

Most occurring characters

Value	Count	Frequency (%)
e	75	11.0%
n	64	9.4%
a	62	9.1%
	52	7.6%
r	41	6.0%
s	32	4.7%
i	32	4.7%
o	31	4.5%
h	30	4.4%
t	25	3.7%
Other values (31)	238	34.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	682	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	75	11.0%
n	64	9.4%
a	62	9.1%
	52	7.6%
r	41	6.0%
s	32	4.7%
i	32	4.7%
o	31	4.5%
h	30	4.4%
t	25	3.7%
Other values (31)	238	34.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	682	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	75	11.0%
n	64	9.4%
a	62	9.1%
	52	7.6%
r	41	6.0%
s	32	4.7%
i	32	4.7%
o	31	4.5%
h	30	4.4%
t	25	3.7%
Other values (31)	238	34.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	682	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	75	11.0%
n	64	9.4%
a	62	9.1%
	52	7.6%
r	41	6.0%
s	32	4.7%
i	32	4.7%
o	31	4.5%
h	30	4.4%
t	25	3.7%
Other values (31)	238	34.9%

ship_address
Categorical

High correlation Missing

Distinct	15
Distinct (%)	31.2%
Missing	464
Missing (%)	90.6%
Memory size	28.8 KiB

123 8th Street	6
123 6th Street	6
123 4th Street	5
789 28th Street	4
123 10th Street	4
Other values (10)	23

Length

Max length	15
Median length	14
Mean length	14.458333
Min length	14

Characters and Unicode

Total characters	694
Distinct characters	18
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	123 12th Street
2nd row	789 27th Street
3rd row	123 4th Street
4th row	123 4th Street
5th row	123 8th Street

Common Values

Value	Count	Frequency (%)
123 8th Street	6	1.2%
123 6th Street	6	1.2%
123 4th Street	5	1.0%
789 28th Street	4	0.8%
123 10th Street	4	0.8%
789 29th Street	4	0.8%
123 3rd Street	3	0.6%
123 1st Street	2	0.4%
789 27th Street	2	0.4%
123 12th Street	2	0.4%
Other values (5)	10	2.0%
(Missing)	464	90.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
street	48	33.3%
123	34	23.6%
789	14	9.7%
8th	6	4.2%
6th	6	4.2%
4th	5	3.5%
28th	4	2.8%
10th	4	2.8%
29th	4	2.8%
3rd	3	2.1%
Other values (8)	16	11.1%

Most occurring characters

Value	Count	Frequency (%)
t	141	20.3%
	96	13.8%
e	96	13.8%
r	51	7.3%
2	50	7.2%
S	48	6.9%
1	46	6.6%
h	43	6.2%
3	37	5.3%
8	24	3.5%
Other values (8)	62	8.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	694	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
t	141	20.3%
	96	13.8%
e	96	13.8%
r	51	7.3%
2	50	7.2%
S	48	6.9%
1	46	6.6%
h	43	6.2%
3	37	5.3%
8	24	3.5%
Other values (8)	62	8.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	694	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
t	141	20.3%
	96	13.8%
e	96	13.8%
r	51	7.3%
2	50	7.2%
S	48	6.9%
1	46	6.6%
h	43	6.2%
3	37	5.3%
8	24	3.5%
Other values (8)	62	8.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	694	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
t	141	20.3%
	96	13.8%
e	96	13.8%
r	51	7.3%
2	50	7.2%
S	48	6.9%
1	46	6.6%
h	43	6.2%
3	37	5.3%
8	24	3.5%
Other values (8)	62	8.9%

ship_city
Categorical

High correlation Missing

Distinct	12
Distinct (%)	25.0%
Missing	464
Missing (%)	90.6%
Memory size	28.5 KiB

Portland	6
Milwaukee	6
Chicago	6
New York	5
Memphis	4
Other values (7)	21

Length

Max length	14
Median length	9
Mean length	7.8541667
Min length	5

Characters and Unicode

Total characters	377
Distinct characters	32
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Las Vegas
2nd row	Las Vegas
3rd row	New York
4th row	New York
5th row	Portland

Common Values

Value	Count	Frequency (%)
Portland	6	1.2%
Milwaukee	6	1.2%
Chicago	6	1.2%
New York	5	1.0%
Memphis	4	0.8%
Las Vegas	4	0.8%
Denver	4	0.8%
Miami	4	0.8%
Los Angelas	3	0.6%
Seattle	2	0.4%
Other values (2)	4	0.8%
(Missing)	464	90.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
portland	6	9.4%
milwaukee	6	9.4%
chicago	6	9.4%
new	5	7.8%
york	5	7.8%
memphis	4	6.2%
las	4	6.2%
vegas	4	6.2%
denver	4	6.2%
miami	4	6.2%
Other values (7)	16	25.0%

Most occurring characters

Value	Count	Frequency (%)
e	44	11.7%
a	39	10.3%
i	28	7.4%
o	22	5.8%
s	20	5.3%
l	19	5.0%
	16	4.2%
r	15	4.0%
t	14	3.7%
M	14	3.7%
Other values (22)	146	38.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	377	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	44	11.7%
a	39	10.3%
i	28	7.4%
o	22	5.8%
s	20	5.3%
l	19	5.0%
	16	4.2%
r	15	4.0%
t	14	3.7%
M	14	3.7%
Other values (22)	146	38.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	377	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	44	11.7%
a	39	10.3%
i	28	7.4%
o	22	5.8%
s	20	5.3%
l	19	5.0%
	16	4.2%
r	15	4.0%
t	14	3.7%
M	14	3.7%
Other values (22)	146	38.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	377	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	44	11.7%
a	39	10.3%
i	28	7.4%
o	22	5.8%
s	20	5.3%
l	19	5.0%
	16	4.2%
r	15	4.0%
t	14	3.7%
M	14	3.7%
Other values (22)	146	38.7%

ship_state_province
Categorical

High correlation Missing

Distinct	12
Distinct (%)	25.0%
Missing	464
Missing (%)	90.6%
Memory size	28.3 KiB

OR	6
WI	6
IL	6
NY	5
TN	4
Other values (7)	21

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	96
Distinct characters	14
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	NV
2nd row	NV
3rd row	NY
4th row	NY
5th row	OR

Common Values

Value	Count	Frequency (%)
OR	6	1.2%
WI	6	1.2%
IL	6	1.2%
NY	5	1.0%
TN	4	0.8%
NV	4	0.8%
CO	4	0.8%
FL	4	0.8%
CA	3	0.6%
WA	2	0.4%
Other values (2)	4	0.8%
(Missing)	464	90.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
or	6	12.5%
wi	6	12.5%
il	6	12.5%
ny	5	10.4%
tn	4	8.3%
nv	4	8.3%
co	4	8.3%
fl	4	8.3%
ca	3	6.2%
wa	2	4.2%
Other values (2)	4	8.3%

Most occurring characters

Value	Count	Frequency (%)
I	14	14.6%
N	13	13.5%
L	10	10.4%
O	10	10.4%
W	8	8.3%
C	7	7.3%
R	6	6.2%
T	6	6.2%
Y	5	5.2%
A	5	5.2%
Other values (4)	12	12.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	96	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
I	14	14.6%
N	13	13.5%
L	10	10.4%
O	10	10.4%
W	8	8.3%
C	7	7.3%
R	6	6.2%
T	6	6.2%
Y	5	5.2%
A	5	5.2%
Other values (4)	12	12.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	96	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
I	14	14.6%
N	13	13.5%
L	10	10.4%
O	10	10.4%
W	8	8.3%
C	7	7.3%
R	6	6.2%
T	6	6.2%
Y	5	5.2%
A	5	5.2%
Other values (4)	12	12.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	96	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
I	14	14.6%
N	13	13.5%
L	10	10.4%
O	10	10.4%
W	8	8.3%
C	7	7.3%
R	6	6.2%
T	6	6.2%
Y	5	5.2%
A	5	5.2%
Other values (4)	12	12.5%

ship_zip_postal_code
Categorical

Constant Missing

Distinct	1
Distinct (%)	2.1%
Missing	464
Missing (%)	90.6%
Memory size	28.4 KiB

99999	48

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	240
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	99999
2nd row	99999
3rd row	99999
4th row	99999
5th row	99999

Common Values

Value	Count	Frequency (%)
99999	48	9.4%
(Missing)	464	90.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
99999	48	100.0%

Most occurring characters

Value	Count	Frequency (%)
9	240	100.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	240	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
9	240	100.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	240	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
9	240	100.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	240	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
9	240	100.0%

ship_country_region
Categorical

Constant Missing

Distinct	1
Distinct (%)	2.1%
Missing	464
Missing (%)	90.6%
Memory size	28.3 KiB

USA	48

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	144
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	USA
2nd row	USA
3rd row	USA
4th row	USA
5th row	USA

Common Values

Value	Count	Frequency (%)
USA	48	9.4%
(Missing)	464	90.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
usa	48	100.0%

Most occurring characters

Value	Count	Frequency (%)
U	48	33.3%
S	48	33.3%
A	48	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	144	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
U	48	33.3%
S	48	33.3%
A	48	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	144	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
U	48	33.3%
S	48	33.3%
A	48	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	144	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
U	48	33.3%
S	48	33.3%
A	48	33.3%

shipping_fee
Real number (ℝ)

High correlation Missing Zeros

Distinct	13
Distinct (%)	17.1%
Missing	436
Missing (%)	85.2%
Infinite	0
Infinite (%)	0.0%
Mean	28.131579

Minimum	0
Maximum	300
Zeros	40
Zeros (%)	7.8%
Negative	0
Negative (%)	0.0%
Memory size	4.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	10
95-th percentile	200
Maximum	300
Range	300
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	65.455602
Coefficient of variation (CV)	2.326766
Kurtosis	8.2873457
Mean	28.131579
Median Absolute Deviation (MAD)	0
Skewness	2.9423851
Sum	2138
Variance	4284.4358
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
0	40	7.8%
5	8	1.6%
200	4	0.8%
7	4	0.8%
50	4	0.8%
40	2	0.4%
4	2	0.4%
12	2	0.4%
10	2	0.4%
300	2	0.4%
Other values (3)	6	1.2%
(Missing)	436	85.2%

Value	Count	Frequency (%)
0	40	7.8%
4	2	0.4%
5	8	1.6%
7	4	0.8%
9	2	0.4%
10	2	0.4%
12	2	0.4%
40	2	0.4%
50	4	0.8%
60	2	0.4%

Value	Count	Frequency (%)
300	2	0.4%
200	4	0.8%
100	2	0.4%
60	2	0.4%
50	4	0.8%
40	2	0.4%
12	2	0.4%
10	2	0.4%
9	2	0.4%
7	4	0.8%

taxes
Categorical

Constant Missing

Distinct	1
Distinct (%)	1.3%
Missing	436
Missing (%)	85.2%
Memory size	28.4 KiB

0.0	76

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	228
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	76	14.8%
(Missing)	436	85.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0.0	76	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	152	66.7%
.	76	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	228	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	152	66.7%
.	76	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	228	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	152	66.7%
.	76	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	228	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	152	66.7%
.	76	33.3%

payment_type
Categorical

High correlation Missing

Distinct	3
Distinct (%)	7.9%
Missing	474
Missing (%)	92.6%
Memory size	28.4 KiB

Check	18
Credit Card	16
Cash	4

Length

Max length	11
Median length	5
Mean length	7.4210526
Min length	4

Characters and Unicode

Total characters	282
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Credit Card
2nd row	Check
3rd row	Credit Card
4th row	Check
5th row	Credit Card

Common Values

Value	Count	Frequency (%)
Check	18	3.5%
Credit Card	16	3.1%
Cash	4	0.8%
(Missing)	474	92.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
check	18	33.3%
credit	16	29.6%
card	16	29.6%
cash	4	7.4%

Most occurring characters

Value	Count	Frequency (%)
C	54	19.1%
e	34	12.1%
d	32	11.3%
r	32	11.3%
h	22	7.8%
a	20	7.1%
c	18	6.4%
k	18	6.4%
i	16	5.7%
t	16	5.7%
Other values (2)	20	7.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	282	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
C	54	19.1%
e	34	12.1%
d	32	11.3%
r	32	11.3%
h	22	7.8%
a	20	7.1%
c	18	6.4%
k	18	6.4%
i	16	5.7%
t	16	5.7%
Other values (2)	20	7.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	282	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
C	54	19.1%
e	34	12.1%
d	32	11.3%
r	32	11.3%
h	22	7.8%
a	20	7.1%
c	18	6.4%
k	18	6.4%
i	16	5.7%
t	16	5.7%
Other values (2)	20	7.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	282	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
C	54	19.1%
e	34	12.1%
d	32	11.3%
r	32	11.3%
h	22	7.8%
a	20	7.1%
c	18	6.4%
k	18	6.4%
i	16	5.7%
t	16	5.7%
Other values (2)	20	7.1%

paid_date
Date

Missing

Distinct	26
Distinct (%)	68.4%
Missing	474
Missing (%)	92.6%
Memory size	4.1 KiB

Minimum	2006-01-15 00:00:00
Maximum	2006-06-23 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=26)

tax_rate
Categorical

Constant Missing

Distinct	1
Distinct (%)	2.1%
Missing	464
Missing (%)	90.6%
Memory size	28.3 KiB

0.0	48

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	144
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	48	9.4%
(Missing)	464	90.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0.0	48	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	96	66.7%
.	48	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	144	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	96	66.7%
.	48	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	144	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	96	66.7%
.	48	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	144	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	96	66.7%
.	48	33.3%

tax_status_id
Unsupported

Missing Rejected Unsupported

Missing	512
Missing (%)	100.0%
Memory size	4.6 KiB

status_name
Text

Missing

Distinct	4
Distinct (%)	100.0%
Missing	508
Missing (%)	99.2%
Memory size	16.2 KiB

Length

Max length	8
Median length	6.5
Mean length	6
Min length	3

Characters and Unicode

Total characters	24
Distinct characters	16
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	100.0%

Sample

1st row	New
2nd row	Invoiced
3rd row	Shipped
4th row	Closed

Value	Count	Frequency (%)
new	1	25.0%
invoiced	1	25.0%
shipped	1	25.0%
closed	1	25.0%

Most occurring characters

Value	Count	Frequency (%)
e	4	16.7%
d	3	12.5%
o	2	8.3%
i	2	8.3%
p	2	8.3%
w	1	4.2%
I	1	4.2%
N	1	4.2%
n	1	4.2%
v	1	4.2%
Other values (6)	6	25.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	24	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	4	16.7%
d	3	12.5%
o	2	8.3%
i	2	8.3%
p	2	8.3%
w	1	4.2%
I	1	4.2%
N	1	4.2%
n	1	4.2%
v	1	4.2%
Other values (6)	6	25.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	24	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	4	16.7%
d	3	12.5%
o	2	8.3%
i	2	8.3%
p	2	8.3%
w	1	4.2%
I	1	4.2%
N	1	4.2%
n	1	4.2%
v	1	4.2%
Other values (6)	6	25.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	24	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	4	16.7%
d	3	12.5%
o	2	8.3%
i	2	8.3%
p	2	8.3%
w	1	4.2%
I	1	4.2%
N	1	4.2%
n	1	4.2%
v	1	4.2%
Other values (6)	6	25.0%

tax_status_name
Text

Missing

Distinct	2
Distinct (%)	100.0%
Missing	510
Missing (%)	99.6%
Memory size	16.2 KiB

Length

Max length	10
Median length	8.5
Mean length	8.5
Min length	7

Characters and Unicode

Total characters	17
Distinct characters	11
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	Tax Exempt
2nd row	Taxable

Value	Count	Frequency (%)
tax	1	33.3%
exempt	1	33.3%
taxable	1	33.3%

Most occurring characters

Value	Count	Frequency (%)
a	3	17.6%
x	3	17.6%
T	2	11.8%
e	2	11.8%
	1	5.9%
E	1	5.9%
m	1	5.9%
p	1	5.9%
t	1	5.9%
b	1	5.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	17	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	3	17.6%
x	3	17.6%
T	2	11.8%
e	2	11.8%
	1	5.9%
E	1	5.9%
m	1	5.9%
p	1	5.9%
t	1	5.9%
b	1	5.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	17	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	3	17.6%
x	3	17.6%
T	2	11.8%
e	2	11.8%
	1	5.9%
E	1	5.9%
m	1	5.9%
p	1	5.9%
t	1	5.9%
b	1	5.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	17	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	3	17.6%
x	3	17.6%
T	2	11.8%
e	2	11.8%
	1	5.9%
E	1	5.9%
m	1	5.9%
p	1	5.9%
t	1	5.9%
b	1	5.9%

privilege_name
Text

Constant Missing

Distinct	1
Distinct (%)	100.0%
Missing	511
Missing (%)	99.8%
Memory size	16.2 KiB

Length

Max length	18
Median length	18
Mean length	18
Min length	18

Characters and Unicode

Total characters	18
Distinct characters	14
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	100.0%

Sample

1st row	Purchase Approvals

Value	Count	Frequency (%)
purchase	1	50.0%
approvals	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
a	2	11.1%
r	2	11.1%
p	2	11.1%
s	2	11.1%
u	1	5.6%
P	1	5.6%
h	1	5.6%
c	1	5.6%
	1	5.6%
e	1	5.6%
Other values (4)	4	22.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	18	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	2	11.1%
r	2	11.1%
p	2	11.1%
s	2	11.1%
u	1	5.6%
P	1	5.6%
h	1	5.6%
c	1	5.6%
	1	5.6%
e	1	5.6%
Other values (4)	4	22.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	18	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	2	11.1%
r	2	11.1%
p	2	11.1%
s	2	11.1%
u	1	5.6%
P	1	5.6%
h	1	5.6%
c	1	5.6%
	1	5.6%
e	1	5.6%
Other values (4)	4	22.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	18	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	2	11.1%
r	2	11.1%
p	2	11.1%
s	2	11.1%
u	1	5.6%
P	1	5.6%
h	1	5.6%
c	1	5.6%
	1	5.6%
e	1	5.6%
Other values (4)	4	22.2%

supplier_ids
Categorical

High correlation Missing

Distinct	12
Distinct (%)	26.7%
Missing	467
Missing (%)	91.2%
Memory size	28.2 KiB

6	11
1	9
10	5
7	4
2;6	4
Other values (7)	12

Length

Max length	3
Median length	1
Mean length	1.3333333
Min length	1

Characters and Unicode

Total characters	60
Distinct characters	11
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	8.9%

Sample

1st row	6
2nd row	6
3rd row	6
4th row	6
5th row	6

Common Values

Value	Count	Frequency (%)
6	11	2.1%
1	9	1.8%
10	5	1.0%
7	4	0.8%
2;6	4	0.8%
2	3	0.6%
8	3	0.6%
4	2	0.4%
9	1	0.2%
5	1	0.2%
Other values (2)	2	0.4%
(Missing)	467	91.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
6	11	24.4%
1	9	20.0%
10	5	11.1%
7	4	8.9%
2;6	4	8.9%
2	3	6.7%
8	3	6.7%
4	2	4.4%
9	1	2.2%
5	1	2.2%
Other values (2)	2	4.4%

Most occurring characters

Value	Count	Frequency (%)
6	15	25.0%
1	14	23.3%
2	7	11.7%
0	5	8.3%
;	5	8.3%
7	4	6.7%
8	3	5.0%
4	3	5.0%
3	2	3.3%
9	1	1.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	60	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
6	15	25.0%
1	14	23.3%
2	7	11.7%
0	5	8.3%
;	5	8.3%
7	4	6.7%
8	3	5.0%
4	3	5.0%
3	2	3.3%
9	1	1.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	60	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
6	15	25.0%
1	14	23.3%
2	7	11.7%
0	5	8.3%
;	5	8.3%
7	4	6.7%
8	3	5.0%
4	3	5.0%
3	2	3.3%
9	1	1.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	60	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
6	15	25.0%
1	14	23.3%
2	7	11.7%
0	5	8.3%
;	5	8.3%
7	4	6.7%
8	3	5.0%
4	3	5.0%
3	2	3.3%
9	1	1.7%

product_code
Text

Missing

Distinct	43
Distinct (%)	95.6%
Missing	467
Missing (%)	91.2%
Memory size	17.6 KiB

Length

Max length	9
Median length	8
Mean length	7.8666667
Min length	6

Characters and Unicode

Total characters	354
Distinct characters	26
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	41 ?
Unique (%)	91.1%

Sample

1st row	NWTCFV-88
2nd row	NWTCFV-89
3rd row	NWTCFV-93
4th row	NWTCFV-94
5th row	NWTCFV-92

Value	Count	Frequency (%)
nwtc-82	2	4.4%
nwtjp-6	2	4.4%
nwtcfv-89	1	2.2%
nwtcfv-93	1	2.2%
nwtcfv-94	1	2.2%
nwtcfv-91	1	2.2%
nwtcfv-92	1	2.2%
nwtcfv-90	1	2.2%
nwtb-87	1	2.2%
nwtcm-96	1	2.2%
Other values (33)	33	73.3%

Most occurring characters

Value	Count	Frequency (%)
N	50	14.1%
W	45	12.7%
T	45	12.7%
-	45	12.7%
C	18	5.1%
8	14	4.0%
F	13	3.7%
9	12	3.4%
4	9	2.5%
1	9	2.5%
Other values (16)	94	26.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	354	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	50	14.1%
W	45	12.7%
T	45	12.7%
-	45	12.7%
C	18	5.1%
8	14	4.0%
F	13	3.7%
9	12	3.4%
4	9	2.5%
1	9	2.5%
Other values (16)	94	26.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	354	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	50	14.1%
W	45	12.7%
T	45	12.7%
-	45	12.7%
C	18	5.1%
8	14	4.0%
F	13	3.7%
9	12	3.4%
4	9	2.5%
1	9	2.5%
Other values (16)	94	26.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	354	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	50	14.1%
W	45	12.7%
T	45	12.7%
-	45	12.7%
C	18	5.1%
8	14	4.0%
F	13	3.7%
9	12	3.4%
4	9	2.5%
1	9	2.5%
Other values (16)	94	26.6%

product_name
Text

Missing

Distinct	45
Distinct (%)	100.0%
Missing	467
Missing (%)	91.2%
Memory size	18.4 KiB

Length

Max length	40
Median length	33
Mean length	27.8
Min length	21

Characters and Unicode

Total characters	1251
Distinct characters	43
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	45 ?
Unique (%)	100.0%

Sample

1st row	Northwind Traders Pears
2nd row	Northwind Traders Peaches
3rd row	Northwind Traders Corn
4th row	Northwind Traders Peas
5th row	Northwind Traders Green Beans

Value	Count	Frequency (%)
northwind	45	27.4%
traders	45	27.4%
mix	3	1.8%
dried	3	1.8%
sauce	3	1.8%
chocolate	2	1.2%
tea	2	1.2%
pears	2	1.2%
hot	2	1.2%
green	2	1.2%
Other values (54)	55	33.5%

Most occurring characters

Value	Count	Frequency (%)
r	163	13.0%
	119	9.5%
d	99	7.9%
e	96	7.7%
a	84	6.7%
o	73	5.8%
i	72	5.8%
n	66	5.3%
s	62	5.0%
t	59	4.7%
Other values (33)	358	28.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1251	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
r	163	13.0%
	119	9.5%
d	99	7.9%
e	96	7.7%
a	84	6.7%
o	73	5.8%
i	72	5.8%
n	66	5.3%
s	62	5.0%
t	59	4.7%
Other values (33)	358	28.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1251	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
r	163	13.0%
	119	9.5%
d	99	7.9%
e	96	7.7%
a	84	6.7%
o	73	5.8%
i	72	5.8%
n	66	5.3%
s	62	5.0%
t	59	4.7%
Other values (33)	358	28.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1251	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
r	163	13.0%
	119	9.5%
d	99	7.9%
e	96	7.7%
a	84	6.7%
o	73	5.8%
i	72	5.8%
n	66	5.3%
s	62	5.0%
t	59	4.7%
Other values (33)	358	28.6%

description
Unsupported

Missing Rejected Unsupported

Missing	512
Missing (%)	100.0%
Memory size	4.1 KiB

standard_cost
Real number (ℝ)

High correlation Missing

Distinct	29
Distinct (%)	64.4%
Missing	467
Missing (%)	91.2%
Infinite	0
Infinite (%)	0.0%
Mean	11.6825

Minimum	0.5
Maximum	60.75
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.1 KiB

Quantile statistics

Minimum	0.5
5-th percentile	1
Q1	2
median	7.5
Q3	16.0125
95-th percentile	33.6
Maximum	60.75
Range	60.25
Interquartile range (IQR)	14.0125

Descriptive statistics

Standard deviation	12.689461
Coefficient of variation (CV)	1.086194
Kurtosis	4.0544357
Mean	11.6825
Median Absolute Deviation (MAD)	6.5
Skewness	1.7941241
Sum	525.7125
Variance	161.02242
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
1	9	1.8%
2	4	0.8%
7.5	3	0.6%
3	2	0.4%
0.5	2	0.4%
10.5	2	0.4%
6.9	1	0.2%
9	1	0.2%
16.0125	1	0.2%
29.25	1	0.2%
Other values (19)	19	3.7%
(Missing)	467	91.2%

Value	Count	Frequency (%)
0.5	2	0.4%
1	9	1.8%
2	4	0.8%
3	2	0.4%
5.25	1	0.2%
6.9	1	0.2%
7.2375	1	0.2%
7.5	3	0.6%
9	1	0.2%
9.5625	1	0.2%

Value	Count	Frequency (%)
60.75	1	0.2%
39.75	1	0.2%
34.5	1	0.2%
30	1	0.2%
29.25	1	0.2%
28.5	1	0.2%
26.1	1	0.2%
22.5	1	0.2%
18.75	1	0.2%
17.4375	1	0.2%

list_price
Real number (ℝ)

High correlation Missing

Distinct	37
Distinct (%)	82.2%
Missing	467
Missing (%)	91.2%
Infinite	0
Infinite (%)	0.0%
Mean	15.845778

Minimum	1.2
Maximum	81
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.1 KiB

Quantile statistics

Minimum	1.2
5-th percentile	1.34
Q1	2.99
median	10
Q3	21.35
95-th percentile	44.8
Maximum	81
Range	79.8
Interquartile range (IQR)	18.36

Descriptive statistics

Standard deviation	16.743022
Coefficient of variation (CV)	1.0566236
Kurtosis	4.2057324
Mean	15.845778
Median Absolute Deviation (MAD)	8.11
Skewness	1.8263175
Sum	713.06
Variance	280.3288
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=37)

Value	Count	Frequency (%)
4	3	0.6%
10	3	0.6%
1.2	2	0.4%
2	2	0.4%
1.5	2	0.4%
1.8	2	0.4%
1.3	1	0.2%
1.89	1	0.2%
5	1	0.2%
1.95	1	0.2%
Other values (27)	27	5.3%
(Missing)	467	91.2%

Value	Count	Frequency (%)
1.2	2	0.4%
1.3	1	0.2%
1.5	2	0.4%
1.8	2	0.4%
1.89	1	0.2%
1.95	1	0.2%
2	2	0.4%
2.99	1	0.2%
3.5	1	0.2%
4	3	0.6%

Value	Count	Frequency (%)
81	1	0.2%
53	1	0.2%
46	1	0.2%
40	1	0.2%
39	1	0.2%
38	1	0.2%
34.8	1	0.2%
30	1	0.2%
25	1	0.2%
23.25	1	0.2%

reorder_level
Real number (ℝ)

High correlation Missing

Distinct	8
Distinct (%)	17.8%
Missing	467
Missing (%)	91.2%
Infinite	0
Infinite (%)	0.0%
Mean	22.444444

Minimum	5
Maximum	100
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	5
5-th percentile	6
Q1	10
median	10
Q3	25
95-th percentile	90
Maximum	100
Range	95
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	23.442924
Coefficient of variation (CV)	1.0444867
Kurtosis	6.3139457
Mean	22.444444
Median Absolute Deviation (MAD)	5
Skewness	2.5591877
Sum	1010
Variance	549.57071
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
10	21	4.1%
30	5	1.0%
25	5	1.0%
20	4	0.8%
5	3	0.6%
100	3	0.6%
50	2	0.4%
15	2	0.4%
(Missing)	467	91.2%

Value	Count	Frequency (%)
5	3	0.6%
10	21	4.1%
15	2	0.4%
20	4	0.8%
25	5	1.0%
30	5	1.0%
50	2	0.4%
100	3	0.6%

Value	Count	Frequency (%)
100	3	0.6%
50	2	0.4%
30	5	1.0%
25	5	1.0%
20	4	0.8%
15	2	0.4%
10	21	4.1%
5	3	0.6%

target_level
Real number (ℝ)

High correlation Missing

Distinct	10
Distinct (%)	22.2%
Missing	467
Missing (%)	91.2%
Infinite	0
Infinite (%)	0.0%
Mean	69.555556

Minimum	20
Maximum	200
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	20
5-th percentile	20
Q1	40
median	40
Q3	100
95-th percentile	200
Maximum	200
Range	180
Interquartile range (IQR)	60

Descriptive statistics

Standard deviation	50.506775
Coefficient of variation (CV)	0.72613575
Kurtosis	1.7112448
Mean	69.555556
Median Absolute Deviation (MAD)	20
Skewness	1.5422159
Sum	3130
Variance	2550.9343
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
40	19	3.7%
100	6	1.2%
20	5	1.0%
200	4	0.8%
50	3	0.6%
60	2	0.4%
80	2	0.4%
120	2	0.4%
125	1	0.2%
75	1	0.2%
(Missing)	467	91.2%

Value	Count	Frequency (%)
20	5	1.0%
40	19	3.7%
50	3	0.6%
60	2	0.4%
75	1	0.2%
80	2	0.4%
100	6	1.2%
120	2	0.4%
125	1	0.2%
200	4	0.8%

Value	Count	Frequency (%)
200	4	0.8%
125	1	0.2%
120	2	0.4%
100	6	1.2%
80	2	0.4%
75	1	0.2%
60	2	0.4%
50	3	0.6%
40	19	3.7%
20	5	1.0%

quantity_per_unit
Text

Missing

Distinct	32
Distinct (%)	80.0%
Missing	472
Missing (%)	92.2%
Memory size	17.6 KiB

Length

Max length	20
Median length	17.5
Mean length	12.25
Min length	4

Characters and Unicode

Total characters	490
Distinct characters	33
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	28 ?
Unique (%)	70.0%

Sample

1st row	15.25 OZ
2nd row	15.25 OZ
3rd row	14.5 OZ
4th row	14.5 OZ
5th row	14.5 OZ

Value	Count	Frequency (%)
oz	18	12.2%
	17	11.6%
12	10	6.8%
pkgs	8	5.4%
boxes	8	5.4%
24	7	4.8%
g	6	4.1%
15.25	5	3.4%
jars	4	2.7%
14.5	3	2.0%
Other values (37)	61	41.5%

Most occurring characters

Value	Count	Frequency (%)
	107	21.8%
s	30	6.1%
2	29	5.9%
1	27	5.5%
o	24	4.9%
5	22	4.5%
g	21	4.3%
0	21	4.3%
b	18	3.7%
-	17	3.5%
Other values (23)	174	35.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	490	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	107	21.8%
s	30	6.1%
2	29	5.9%
1	27	5.5%
o	24	4.9%
5	22	4.5%
g	21	4.3%
0	21	4.3%
b	18	3.7%
-	17	3.5%
Other values (23)	174	35.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	490	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	107	21.8%
s	30	6.1%
2	29	5.9%
1	27	5.5%
o	24	4.9%
5	22	4.5%
g	21	4.3%
0	21	4.3%
b	18	3.7%
-	17	3.5%
Other values (23)	174	35.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	490	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	107	21.8%
s	30	6.1%
2	29	5.9%
1	27	5.5%
o	24	4.9%
5	22	4.5%
g	21	4.3%
0	21	4.3%
b	18	3.7%
-	17	3.5%
Other values (23)	174	35.5%

discontinued
Categorical

Constant Missing

Distinct	1
Distinct (%)	2.2%
Missing	467
Missing (%)	91.2%
Memory size	28.2 KiB

0	45

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	45
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	45	8.8%
(Missing)	467	91.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	45	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	45	100.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	45	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	45	100.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	45	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	45	100.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	45	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	45	100.0%

minimum_reorder_quantity
Real number (ℝ)

High correlation Missing

Distinct	6
Distinct (%)	20.0%
Missing	482
Missing (%)	94.1%
Infinite	0
Infinite (%)	0.0%
Mean	15

Minimum	5
Maximum	30
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	5
5-th percentile	5
Q1	10
median	10
Q3	25
95-th percentile	27.75
Maximum	30
Range	25
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	8.304548
Coefficient of variation (CV)	0.55363653
Kurtosis	-1.2860119
Mean	15
Median Absolute Deviation (MAD)	5
Skewness	0.48381407
Sum	450
Variance	68.965517
Monotonicity	Increasing

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
10	12	2.3%
25	7	1.4%
5	5	1.0%
15	2	0.4%
20	2	0.4%
30	2	0.4%
(Missing)	482	94.1%

Value	Count	Frequency (%)
5	5	1.0%
10	12	2.3%
15	2	0.4%
20	2	0.4%
25	7	1.4%
30	2	0.4%

Value	Count	Frequency (%)
30	2	0.4%
25	7	1.4%
20	2	0.4%
15	2	0.4%
10	12	2.3%
5	5	1.0%

category
Categorical

High correlation Missing

Distinct	16
Distinct (%)	35.6%
Missing	467
Missing (%)	91.2%
Memory size	28.8 KiB

Canned Fruit & Vegetables	8
Beverages	5
Dried Fruit & Nuts	5
Baked Goods & Mixes	4
Soups	3
Other values (11)	20

Length

Max length	31
Median length	18
Mean length	13.711111
Min length	3

Characters and Unicode

Total characters	617
Distinct characters	40
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	11.1%

Sample

1st row	Canned Fruit & Vegetables
2nd row	Canned Fruit & Vegetables
3rd row	Canned Fruit & Vegetables
4th row	Canned Fruit & Vegetables
5th row	Canned Fruit & Vegetables

Common Values

Value	Count	Frequency (%)
Canned Fruit & Vegetables	8	1.6%
Beverages	5	1.0%
Dried Fruit & Nuts	5	1.0%
Baked Goods & Mixes	4	0.8%
Soups	3	0.6%
Canned Meat	3	0.6%
Sauces	3	0.6%
Condiments	3	0.6%
Jams, Preserves	2	0.4%
Cereal	2	0.4%
Other values (6)	7	1.4%
(Missing)	467	91.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
	17	16.5%
fruit	13	12.6%
canned	11	10.7%
vegetables	8	7.8%
beverages	5	4.9%
dried	5	4.9%
nuts	5	4.9%
baked	4	3.9%
goods	4	3.9%
mixes	4	3.9%
Other values (15)	27	26.2%

Most occurring characters

Value	Count	Frequency (%)
e	82	13.3%
	58	9.4%
s	47	7.6%
a	46	7.5%
t	36	5.8%
n	33	5.3%
r	33	5.3%
d	31	5.0%
i	30	4.9%
u	25	4.1%
Other values (30)	196	31.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	617	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	82	13.3%
	58	9.4%
s	47	7.6%
a	46	7.5%
t	36	5.8%
n	33	5.3%
r	33	5.3%
d	31	5.0%
i	30	4.9%
u	25	4.1%
Other values (30)	196	31.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	617	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	82	13.3%
	58	9.4%
s	47	7.6%
a	46	7.5%
t	36	5.8%
n	33	5.3%
r	33	5.3%
d	31	5.0%
i	30	4.9%
u	25	4.1%
Other values (30)	196	31.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	617	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	82	13.3%
	58	9.4%
s	47	7.6%
a	46	7.5%
t	36	5.8%
n	33	5.3%
r	33	5.3%
d	31	5.0%
i	30	4.9%
u	25	4.1%
Other values (30)	196	31.8%

unit_cost
Real number (ℝ)

High correlation Missing

Distinct	25
Distinct (%)	45.5%
Missing	457
Missing (%)	89.3%
Infinite	0
Infinite (%)	0.0%
Mean	17.495455

Minimum	2
Maximum	61
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.1 KiB

Quantile statistics

Minimum	2
5-th percentile	4.4
Q1	8
median	14
Q3	26
95-th percentile	39.3
Maximum	61
Range	59
Interquartile range (IQR)	18

Descriptive statistics

Standard deviation	13.068772
Coefficient of variation (CV)	0.746981
Kurtosis	2.5373064
Mean	17.495455
Median Absolute Deviation (MAD)	7
Skewness	1.5316538
Sum	962.25
Variance	170.7928
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=25)

Value	Count	Frequency (%)
7	8	1.6%
10	7	1.4%
34	4	0.8%
8	4	0.8%
16	4	0.8%
26	3	0.6%
14	3	0.6%
30	2	0.4%
15	2	0.4%
2	2	0.4%
Other values (15)	16	3.1%
(Missing)	457	89.3%

Value	Count	Frequency (%)
2	2	0.4%
3	1	0.2%
5	1	0.2%
7	8	1.6%
8	4	0.8%
9	1	0.2%
10	7	1.4%
13	2	0.4%
13.5	1	0.2%
14	3	0.6%

Value	Count	Frequency (%)
61	1	0.2%
60	1	0.2%
40	1	0.2%
39	1	0.2%
34	4	0.8%
30	2	0.4%
29	1	0.2%
28	1	0.2%
26	3	0.6%
22	1	0.2%

date_received
Date

Missing

Distinct	6
Distinct (%)	14.0%
Missing	469
Missing (%)	91.6%
Memory size	4.1 KiB

Minimum	2006-01-22 00:00:00
Maximum	2006-04-17 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=6)

posted_to_inventory
Categorical

High correlation Missing

Distinct	2
Distinct (%)	3.6%
Missing	457
Missing (%)	89.3%
Memory size	28.2 KiB

1	43
0	12

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	55
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	43	8.4%
0	12	2.3%
(Missing)	457	89.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	43	78.2%
0	12	21.8%

Most occurring characters

Value	Count	Frequency (%)
1	43	78.2%
0	12	21.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	55	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
1	43	78.2%
0	12	21.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	55	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
1	43	78.2%
0	12	21.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	55	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
1	43	78.2%
0	12	21.8%

supplier_id
Real number (ℝ)

High correlation Missing

Distinct	8
Distinct (%)	28.6%
Missing	484
Missing (%)	94.5%
Infinite	0
Infinite (%)	0.0%
Mean	3.1785714

Minimum	1
Maximum	8
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	5
95-th percentile	7.65
Maximum	8
Range	7
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.3262364
Coefficient of variation (CV)	0.73184965
Kurtosis	-0.65458685
Mean	3.1785714
Median Absolute Deviation (MAD)	1
Skewness	0.85097162
Sum	89
Variance	5.4113757
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
2	9	1.8%
1	8	1.6%
6	3	0.6%
5	3	0.6%
8	2	0.4%
4	1	0.2%
3	1	0.2%
7	1	0.2%
(Missing)	484	94.5%

Value	Count	Frequency (%)
1	8	1.6%
2	9	1.8%
3	1	0.2%
4	1	0.2%
5	3	0.6%
6	3	0.6%
7	1	0.2%
8	2	0.4%

Value	Count	Frequency (%)
8	2	0.4%
7	1	0.2%
6	3	0.6%
5	3	0.6%
4	1	0.2%
3	1	0.2%
2	9	1.8%
1	8	1.6%

created_by
Real number (ℝ)

High correlation Missing

Distinct	8
Distinct (%)	32.0%
Missing	487
Missing (%)	95.1%
Infinite	0
Infinite (%)	0.0%
Mean	3.36

Minimum	1
Maximum	9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	2
Q3	4
95-th percentile	7
Maximum	9
Range	8
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	2.2338308
Coefficient of variation (CV)	0.66483059
Kurtosis	0.29415092
Mean	3.36
Median Absolute Deviation (MAD)	1
Skewness	1.1396509
Sum	84
Variance	4.99
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
2	11	2.1%
7	3	0.6%
1	3	0.6%
4	3	0.6%
3	2	0.4%
5	1	0.2%
9	1	0.2%
6	1	0.2%
(Missing)	487	95.1%

Value	Count	Frequency (%)
1	3	0.6%
2	11	2.1%
3	2	0.4%
4	3	0.6%
5	1	0.2%
6	1	0.2%
7	3	0.6%
9	1	0.2%

Value	Count	Frequency (%)
9	1	0.2%
7	3	0.6%
6	1	0.2%
5	1	0.2%
4	3	0.6%
3	2	0.4%
2	11	2.1%
1	3	0.6%

submitted_date
Date

Missing

Distinct	7
Distinct (%)	25.0%
Missing	484
Missing (%)	94.5%
Memory size	4.1 KiB

Minimum	2006-01-14 00:00:00
Maximum	2006-04-26 18:33:52
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=7)

creation_date
Date

Missing

Distinct	9
Distinct (%)	32.1%
Missing	484
Missing (%)	94.5%
Memory size	4.1 KiB

Minimum	2006-01-22 00:00:00
Maximum	2006-04-26 18:33:52
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=9)

expected_date
Unsupported

Missing Rejected Unsupported

Missing	512
Missing (%)	100.0%
Memory size	4.1 KiB

payment_date
Unsupported

Missing Rejected Unsupported

Missing	512
Missing (%)	100.0%
Memory size	4.1 KiB

payment_amount
Categorical

Constant Missing

Distinct	1
Distinct (%)	3.6%
Missing	484
Missing (%)	94.5%
Memory size	28.2 KiB

0.0	28

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	84
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	28	5.5%
(Missing)	484	94.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0.0	28	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	56	66.7%
.	28	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	84	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	56	66.7%
.	28	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	84	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	56	66.7%
.	28	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	84	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	56	66.7%
.	28	33.3%

payment_method
Text

Constant Missing

Distinct	1
Distinct (%)	50.0%
Missing	510
Missing (%)	99.6%
Memory size	16.2 KiB

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	10
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Check
2nd row	Check

Value	Count	Frequency (%)
check	2	100.0%

Most occurring characters

Value	Count	Frequency (%)
C	2	20.0%
h	2	20.0%
e	2	20.0%
c	2	20.0%
k	2	20.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	10	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
C	2	20.0%
h	2	20.0%
e	2	20.0%
c	2	20.0%
k	2	20.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	10	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
C	2	20.0%
h	2	20.0%
e	2	20.0%
c	2	20.0%
k	2	20.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	10	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
C	2	20.0%
h	2	20.0%
e	2	20.0%
c	2	20.0%
k	2	20.0%

approved_by
Categorical

Constant Missing

Distinct	1
Distinct (%)	4.0%
Missing	487
Missing (%)	95.1%
Memory size	28.2 KiB

2	25

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	25
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	2
3rd row	2
4th row	2
5th row	2

Common Values

Value	Count	Frequency (%)
2	25	4.9%
(Missing)	487	95.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2	25	100.0%

Most occurring characters

Value	Count	Frequency (%)
2	25	100.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	25	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
2	25	100.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	25	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
2	25	100.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	25	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
2	25	100.0%

approved_date
Date

Missing

Distinct	5
Distinct (%)	20.0%
Missing	487
Missing (%)	95.1%
Memory size	4.1 KiB

Minimum	2006-01-22 00:00:00
Maximum	2006-04-25 17:18:51
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=5)

submitted_by
Real number (ℝ)

High correlation Missing

Distinct	8
Distinct (%)	28.6%
Missing	484
Missing (%)	94.5%
Infinite	0
Infinite (%)	0.0%
Mean	3.2142857

Minimum	1
Maximum	9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	2
Q3	4
95-th percentile	7
Maximum	9
Range	8
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	2.149197
Coefficient of variation (CV)	0.66863906
Kurtosis	0.77914337
Mean	3.2142857
Median Absolute Deviation (MAD)	0.5
Skewness	1.3160464
Sum	90
Variance	4.6190476
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
2	14	2.7%
7	3	0.6%
1	3	0.6%
4	3	0.6%
3	2	0.4%
5	1	0.2%
9	1	0.2%
6	1	0.2%
(Missing)	484	94.5%

Value	Count	Frequency (%)
1	3	0.6%
2	14	2.7%
3	2	0.4%
4	3	0.6%
5	1	0.2%
6	1	0.2%
7	3	0.6%
9	1	0.2%

Value	Count	Frequency (%)
9	1	0.2%
7	3	0.6%
6	1	0.2%
5	1	0.2%
4	3	0.6%
3	2	0.4%
2	14	2.7%
1	3	0.6%

group_by
Text

Missing

Distinct	5
Distinct (%)	100.0%
Missing	507
Missing (%)	99.0%
Memory size	16.3 KiB

Length

Max length	14
Median length	11
Mean length	10.8
Min length	8

Characters and Unicode

Total characters	54
Distinct characters	22
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	100.0%

Sample

1st row	country_region
2nd row	Customer ID
3rd row	employee_id
4th row	Category
5th row	Product ID

Value	Count	Frequency (%)
id	2	28.6%
country_region	1	14.3%
customer	1	14.3%
employee_id	1	14.3%
category	1	14.3%
product	1	14.3%

Most occurring characters

Value	Count	Frequency (%)
o	6	11.1%
e	6	11.1%
r	5	9.3%
t	4	7.4%
y	3	5.6%
u	3	5.6%
n	2	3.7%
c	2	3.7%
_	2	3.7%
g	2	3.7%
Other values (12)	19	35.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	54	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	6	11.1%
e	6	11.1%
r	5	9.3%
t	4	7.4%
y	3	5.6%
u	3	5.6%
n	2	3.7%
c	2	3.7%
_	2	3.7%
g	2	3.7%
Other values (12)	19	35.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	54	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	6	11.1%
e	6	11.1%
r	5	9.3%
t	4	7.4%
y	3	5.6%
u	3	5.6%
n	2	3.7%
c	2	3.7%
_	2	3.7%
g	2	3.7%
Other values (12)	19	35.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	54	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	6	11.1%
e	6	11.1%
r	5	9.3%
t	4	7.4%
y	3	5.6%
u	3	5.6%
n	2	3.7%
c	2	3.7%
_	2	3.7%
g	2	3.7%
Other values (12)	19	35.2%

display
Text

Missing

Distinct	5
Distinct (%)	100.0%
Missing	507
Missing (%)	99.0%
Memory size	16.3 KiB

Length

Max length	14
Median length	8
Mean length	9
Min length	7

Characters and Unicode

Total characters	45
Distinct characters	21
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	100.0%

Sample

1st row	Country/Region
2nd row	Customer
3rd row	Employee
4th row	Category
5th row	Product

Value	Count	Frequency (%)
country/region	1	20.0%
customer	1	20.0%
employee	1	20.0%
category	1	20.0%
product	1	20.0%

Most occurring characters

Value	Count	Frequency (%)
o	6	13.3%
e	5	11.1%
t	4	8.9%
r	4	8.9%
C	3	6.7%
y	3	6.7%
u	3	6.7%
n	2	4.4%
g	2	4.4%
m	2	4.4%
Other values (11)	11	24.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	45	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	6	13.3%
e	5	11.1%
t	4	8.9%
r	4	8.9%
C	3	6.7%
y	3	6.7%
u	3	6.7%
n	2	4.4%
g	2	4.4%
m	2	4.4%
Other values (11)	11	24.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	45	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	6	13.3%
e	5	11.1%
t	4	8.9%
r	4	8.9%
C	3	6.7%
y	3	6.7%
u	3	6.7%
n	2	4.4%
g	2	4.4%
m	2	4.4%
Other values (11)	11	24.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	45	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	6	13.3%
e	5	11.1%
t	4	8.9%
r	4	8.9%
C	3	6.7%
y	3	6.7%
u	3	6.7%
n	2	4.4%
g	2	4.4%
m	2	4.4%
Other values (11)	11	24.4%

title
Text

Missing

Distinct	5
Distinct (%)	100.0%
Missing	507
Missing (%)	99.0%
Memory size	16.3 KiB

Length

Max length	17
Median length	17
Mean length	16.6
Min length	16

Characters and Unicode

Total characters	83
Distinct characters	22
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	100.0%

Sample

1st row	Sales By Country
2nd row	Sales By Customer
3rd row	Sales By Employee
4th row	Sales By Category
5th row	Sales by Product

Value	Count	Frequency (%)
sales	5	33.3%
by	5	33.3%
country	1	6.7%
customer	1	6.7%
employee	1	6.7%
category	1	6.7%
product	1	6.7%

Most occurring characters

Value	Count	Frequency (%)
	10	12.0%
e	9	10.8%
y	8	9.6%
l	6	7.2%
s	6	7.2%
a	6	7.2%
S	5	6.0%
o	5	6.0%
B	4	4.8%
r	4	4.8%
Other values (12)	20	24.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	83	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	10	12.0%
e	9	10.8%
y	8	9.6%
l	6	7.2%
s	6	7.2%
a	6	7.2%
S	5	6.0%
o	5	6.0%
B	4	4.8%
r	4	4.8%
Other values (12)	20	24.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	83	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	10	12.0%
e	9	10.8%
y	8	9.6%
l	6	7.2%
s	6	7.2%
a	6	7.2%
S	5	6.0%
o	5	6.0%
B	4	4.8%
r	4	4.8%
Other values (12)	20	24.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	83	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	10	12.0%
e	9	10.8%
y	8	9.6%
l	6	7.2%
s	6	7.2%
a	6	7.2%
S	5	6.0%
o	5	6.0%
B	4	4.8%
r	4	4.8%
Other values (12)	20	24.1%

filter_row_source
Text

Missing

Distinct	5
Distinct (%)	100.0%
Missing	507
Missing (%)	99.0%
Memory size	16.7 KiB

Length

Max length	100
Median length	85
Mean length	84.8
Min length	71

Characters and Unicode

Total characters	424
Distinct characters	41
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	100.0%

Sample

1st row	SELECT DISTINCT [country_region] FROM [customers Extended] ORDER BY [country_region];
2nd row	SELECT DISTINCT [Company] FROM [customers Extended] ORDER BY [Company];
3rd row	SELECT DISTINCT [Employee Name] FROM [`dl_northwind`.`employees` Extended] ORDER BY [Employee Name];
4th row	SELECT DISTINCT [Category] FROM [`dl_northwind`.`products`] ORDER BY [Category];
5th row	SELECT DISTINCT [Product Name] FROM [`dl_northwind`.`products`] ORDER BY [Product Name];

Value	Count	Frequency (%)
select	5	10.6%
distinct	5	10.6%
from	5	10.6%
order	5	10.6%
by	5	10.6%
name	4	8.5%
extended	3	6.4%
customers	2	4.3%
country_region	2	4.3%
company	2	4.3%
Other values (5)	9	19.1%

Most occurring characters

Value	Count	Frequency (%)
	42	9.9%
e	23	5.4%
E	20	4.7%
o	20	4.7%
t	16	3.8%
d	16	3.8%
T	15	3.5%
R	15	3.5%
r	15	3.5%
[	15	3.5%
Other values (31)	227	53.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	424	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	42	9.9%
e	23	5.4%
E	20	4.7%
o	20	4.7%
t	16	3.8%
d	16	3.8%
T	15	3.5%
R	15	3.5%
r	15	3.5%
[	15	3.5%
Other values (31)	227	53.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	424	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	42	9.9%
e	23	5.4%
E	20	4.7%
o	20	4.7%
t	16	3.8%
d	16	3.8%
T	15	3.5%
R	15	3.5%
r	15	3.5%
[	15	3.5%
Other values (31)	227	53.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	424	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	42	9.9%
e	23	5.4%
E	20	4.7%
o	20	4.7%
t	16	3.8%
d	16	3.8%
T	15	3.5%
R	15	3.5%
r	15	3.5%
[	15	3.5%
Other values (31)	227	53.5%

default
Categorical

High correlation Missing

Distinct	2
Distinct (%)	40.0%
Missing	507
Missing (%)	99.0%
Memory size	28.1 KiB

0	4
1	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	5
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	20.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	4	0.8%
1	1	0.2%
(Missing)	507	99.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	4	80.0%
1	1	20.0%

Most occurring characters

Value	Count	Frequency (%)
0	4	80.0%
1	1	20.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	5	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	4	80.0%
1	1	20.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	5	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	4	80.0%
1	1	20.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	5	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	4	80.0%
1	1	20.0%

string_id
Real number (ℝ)

High correlation Missing

Distinct	62
Distinct (%)	100.0%
Missing	450
Missing (%)	87.9%
Infinite	0
Infinite (%)	0.0%
Mean	45.306452

Minimum	2
Maximum	114
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.6 KiB

Quantile statistics

Minimum	2
5-th percentile	5.05
Q1	17.25
median	33.5
Q3	48.75
95-th percentile	110.95
Maximum	114
Range	112
Interquartile range (IQR)	31.5

Descriptive statistics

Standard deviation	37.279005
Coefficient of variation (CV)	0.82281891
Kurtosis	-0.76007804
Mean	45.306452
Median Absolute Deviation (MAD)	16
Skewness	0.8729872
Sum	2809
Variance	1389.7242
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
6	1	0.2%
4	1	0.2%
10	1	0.2%
5	1	0.2%
7	1	0.2%
3	1	0.2%
9	1	0.2%
2	1	0.2%
46	1	0.2%
24	1	0.2%
Other values (52)	52	10.2%
(Missing)	450	87.9%

Value	Count	Frequency (%)
2	1	0.2%
3	1	0.2%
4	1	0.2%
5	1	0.2%
6	1	0.2%
7	1	0.2%
8	1	0.2%
9	1	0.2%
10	1	0.2%
11	1	0.2%

Value	Count	Frequency (%)
114	1	0.2%
113	1	0.2%
112	1	0.2%
111	1	0.2%
110	1	0.2%
109	1	0.2%
108	1	0.2%
107	1	0.2%
106	1	0.2%
105	1	0.2%

string_data
Text

Missing

Distinct	62
Distinct (%)	100.0%
Missing	450
Missing (%)	87.9%
Memory size	21.0 KiB

Length

Max length	149
Median length	73
Mean length	54.822581
Min length	17

Characters and Unicode

Total characters	3399
Distinct characters	51
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	62 ?
Unique (%)	100.0%

Sample

1st row	Back ordered product filled for Order #\|
2nd row	Insufficient inventory.
3rd row	Cannot remove posted inventory!
4th row	Must specify customer name!
5th row	Discounted price below cost!

Value	Count	Frequency (%)
to	23	4.6%
order	21	4.2%
inventory	17	3.4%
purchase	17	3.4%
you	16	3.2%
product	15	3.0%
cannot	13	2.6%
for	11	2.2%
must	10	2.0%
successfully	10	2.0%
Other values (147)	350	69.6%

Most occurring characters

Value	Count	Frequency (%)
	451	13.3%
e	343	10.1%
r	257	7.6%
o	249	7.3%
t	222	6.5%
n	194	5.7%
s	179	5.3%
i	166	4.9%
d	148	4.4%
a	147	4.3%
Other values (41)	1043	30.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3399	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	451	13.3%
e	343	10.1%
r	257	7.6%
o	249	7.3%
t	222	6.5%
n	194	5.7%
s	179	5.3%
i	166	4.9%
d	148	4.4%
a	147	4.3%
Other values (41)	1043	30.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3399	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	451	13.3%
e	343	10.1%
r	257	7.6%
o	249	7.3%
t	222	6.5%
n	194	5.7%
s	179	5.3%
i	166	4.9%
d	148	4.4%
a	147	4.3%
Other values (41)	1043	30.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3399	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	451	13.3%
e	343	10.1%
r	257	7.6%
o	249	7.3%
t	222	6.5%
n	194	5.7%
s	179	5.3%
i	166	4.9%
d	148	4.4%
a	147	4.3%
Other values (41)	1043	30.7%

Interactions

Correlations

	__table_name__	category	city	created_by	customer_id	default	employee_id	fax_number	id	inventory_id	job_title	list_price	minimum_reorder_quantity	order_id	payment_type	posted_to_inventory	product_id	purchase_order_id	quantity	reorder_level	ship_address	ship_city	ship_name	ship_state_province	shipper_id	shipping_fee	standard_cost	state_province	status_id	string_id	submitted_by	supplier_id	supplier_ids	target_level	transaction_type	unit_cost	unit_price	web_page
__table_name__	1.000	1.000	0.478	1.000	1.000	1.000	0.196	0.926	0.539	0.699	0.740	1.000	1.000	0.000	1.000	1.000	0.000	0.526	0.149	1.000	1.000	1.000	1.000	1.000	1.000	0.322	1.000	0.539	0.670	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000	1.000
category	1.000	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.378	0.000	0.000	0.107	0.277	0.000	0.000	0.000	0.000	0.000	0.000	0.367	0.000	0.000	0.000	0.000	0.000	0.000	0.231	0.000	0.000	0.000	0.000	0.000	0.709	0.392	0.000	0.000	0.000	0.000
city	0.478	0.000	1.000	0.000	0.000	0.000	0.000	0.535	1.000	0.000	0.175	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.923	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
created_by	1.000	0.000	0.000	1.000	NaN	0.000	NaN	0.000	0.067	NaN	0.000	NaN	NaN	NaN	0.000	0.000	NaN	NaN	NaN	NaN	0.000	0.000	0.000	0.000	0.000	NaN	NaN	0.000	0.000	NaN	1.000	0.011	0.000	NaN	0.000	NaN	NaN	0.000
customer_id	1.000	0.000	0.000	NaN	1.000	0.000	0.091	0.000	-0.039	NaN	0.000	NaN	NaN	NaN	0.637	0.000	NaN	NaN	NaN	NaN	0.886	0.782	0.886	0.782	0.000	0.411	NaN	0.000	0.066	NaN	NaN	NaN	0.000	NaN	0.000	NaN	NaN	0.000
default	1.000	0.000	0.000	0.000	0.000	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
employee_id	0.196	0.000	0.000	NaN	0.091	0.000	1.000	0.000	-0.160	NaN	0.000	NaN	NaN	NaN	0.262	0.000	NaN	NaN	NaN	NaN	0.493	0.464	0.493	0.464	0.453	0.493	NaN	0.000	0.000	NaN	NaN	NaN	0.000	NaN	0.000	NaN	NaN	0.000
fax_number	0.926	0.000	0.535	0.000	0.000	0.000	0.000	1.000	1.000	0.000	0.885	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.561	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000
id	0.539	0.378	1.000	0.067	-0.039	0.000	-0.160	1.000	1.000	-0.170	1.000	-0.743	0.027	0.506	0.000	0.479	-0.025	0.270	0.110	0.305	0.000	0.000	0.000	0.000	0.000	-0.612	-0.755	1.000	0.263	NaN	-0.041	0.278	0.287	0.181	0.500	-0.028	0.115	1.000
inventory_id	0.699	0.000	0.000	NaN	NaN	0.000	NaN	0.000	-0.170	1.000	0.000	NaN	NaN	0.891	0.000	1.000	-0.041	0.737	-0.217	NaN	0.000	0.000	0.000	0.000	0.000	NaN	NaN	0.000	0.459	NaN	NaN	NaN	0.000	NaN	0.000	-0.153	0.158	0.000
job_title	0.740	0.000	0.175	0.000	0.000	0.000	0.000	0.885	1.000	0.000	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
list_price	1.000	0.107	0.000	NaN	NaN	0.000	NaN	0.000	-0.743	NaN	0.000	1.000	-0.017	NaN	0.000	0.000	NaN	NaN	NaN	-0.170	0.000	0.000	0.000	0.000	0.000	NaN	0.984	0.000	0.000	NaN	NaN	NaN	0.428	-0.112	0.000	NaN	NaN	0.000
minimum_reorder_quantity	1.000	0.277	0.000	NaN	NaN	0.000	NaN	0.000	0.027	NaN	0.000	-0.017	1.000	NaN	0.000	0.000	NaN	NaN	NaN	0.956	0.000	0.000	0.000	0.000	0.000	NaN	-0.013	0.000	0.000	NaN	NaN	NaN	0.163	0.987	0.000	NaN	NaN	0.000
order_id	0.000	0.000	0.000	NaN	NaN	0.000	NaN	0.000	0.506	0.891	0.000	NaN	NaN	1.000	0.000	0.000	0.010	0.998	-0.073	NaN	0.000	0.000	0.000	0.000	0.000	NaN	NaN	0.000	0.243	NaN	NaN	NaN	0.000	NaN	0.000	NaN	0.160	0.000
payment_type	1.000	0.000	0.000	0.000	0.637	0.000	0.262	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000	0.000	0.000	0.000	0.000	0.000	0.672	0.530	0.672	0.530	0.120	0.297	0.000	0.000	0.086	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
posted_to_inventory	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.479	1.000	0.000	0.000	0.000	0.000	0.000	1.000	0.000	0.674	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
product_id	0.000	0.000	0.000	NaN	NaN	0.000	NaN	0.000	-0.025	-0.041	0.000	NaN	NaN	0.010	0.000	0.000	1.000	0.185	0.208	NaN	0.000	0.000	0.000	0.000	0.000	NaN	NaN	0.000	0.182	NaN	NaN	NaN	0.000	NaN	0.075	-0.110	-0.335	0.000
purchase_order_id	0.526	0.000	0.000	NaN	NaN	0.000	NaN	0.000	0.270	0.737	0.000	NaN	NaN	0.998	0.000	0.674	0.185	1.000	-0.048	NaN	0.000	0.000	0.000	0.000	0.000	NaN	NaN	0.000	0.000	NaN	NaN	NaN	0.000	NaN	0.000	0.093	0.101	0.000
quantity	0.149	0.000	0.000	NaN	NaN	0.000	NaN	0.000	0.110	-0.217	0.000	NaN	NaN	-0.073	0.000	0.000	0.208	-0.048	1.000	NaN	0.000	0.000	0.000	0.000	0.000	NaN	NaN	0.000	0.000	NaN	NaN	NaN	0.000	NaN	0.238	0.020	-0.040	0.000
reorder_level	1.000	0.367	0.000	NaN	NaN	0.000	NaN	0.000	0.305	NaN	0.000	-0.170	0.956	NaN	0.000	0.000	NaN	NaN	NaN	1.000	0.000	0.000	0.000	0.000	0.000	NaN	-0.223	0.000	0.000	NaN	NaN	NaN	0.246	0.938	0.000	NaN	NaN	0.000
ship_address	1.000	0.000	0.000	0.000	0.886	0.000	0.493	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.672	0.000	0.000	0.000	0.000	0.000	1.000	0.957	1.000	0.957	0.611	0.630	0.000	0.000	0.042	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
ship_city	1.000	0.000	0.000	0.000	0.782	0.000	0.464	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.530	0.000	0.000	0.000	0.000	0.000	0.957	1.000	0.957	1.000	0.646	0.590	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
ship_name	1.000	0.000	0.000	0.000	0.886	0.000	0.493	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.672	0.000	0.000	0.000	0.000	0.000	1.000	0.957	1.000	0.957	0.611	0.630	0.000	0.000	0.042	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
ship_state_province	1.000	0.000	0.000	0.000	0.782	0.000	0.464	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.530	0.000	0.000	0.000	0.000	0.000	0.957	1.000	0.957	1.000	0.646	0.590	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
shipper_id	1.000	0.000	0.000	0.000	0.000	0.000	0.453	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.120	0.000	0.000	0.000	0.000	0.000	0.611	0.646	0.611	0.646	1.000	0.411	0.000	0.000	0.146	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
shipping_fee	0.322	0.000	0.000	NaN	0.411	0.000	0.493	0.000	-0.612	NaN	0.000	NaN	NaN	NaN	0.297	0.000	NaN	NaN	NaN	NaN	0.630	0.590	0.630	0.590	0.411	1.000	NaN	0.000	0.243	NaN	NaN	NaN	0.000	NaN	0.000	NaN	NaN	0.000
standard_cost	1.000	0.231	0.000	NaN	NaN	0.000	NaN	0.000	-0.755	NaN	0.000	0.984	-0.013	NaN	0.000	0.000	NaN	NaN	NaN	-0.223	0.000	0.000	0.000	0.000	0.000	NaN	1.000	0.000	0.000	NaN	NaN	NaN	0.427	-0.153	0.000	NaN	NaN	0.000
state_province	0.539	0.000	0.923	0.000	0.000	0.000	0.000	0.561	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000
status_id	0.670	0.000	0.000	0.000	0.066	0.000	0.000	0.000	0.263	0.459	0.000	0.000	0.000	0.243	0.086	0.000	0.182	0.000	0.000	0.000	0.042	0.000	0.042	0.000	0.146	0.243	0.000	0.000	1.000	0.000	0.000	0.408	0.000	0.000	0.000	0.000	0.000	0.000
string_id	1.000	0.000	0.000	NaN	NaN	0.000	NaN	0.000	NaN	NaN	0.000	NaN	NaN	NaN	0.000	0.000	NaN	NaN	NaN	NaN	0.000	0.000	0.000	0.000	0.000	NaN	NaN	0.000	0.000	1.000	NaN	NaN	0.000	NaN	0.000	NaN	NaN	0.000
submitted_by	1.000	0.000	0.000	1.000	NaN	0.000	NaN	0.000	-0.041	NaN	0.000	NaN	NaN	NaN	0.000	0.000	NaN	NaN	NaN	NaN	0.000	0.000	0.000	0.000	0.000	NaN	NaN	0.000	0.000	NaN	1.000	-0.096	0.000	NaN	0.000	NaN	NaN	0.000
supplier_id	1.000	0.000	0.000	0.011	NaN	0.000	NaN	0.000	0.278	NaN	0.000	NaN	NaN	NaN	0.000	0.000	NaN	NaN	NaN	NaN	0.000	0.000	0.000	0.000	0.000	NaN	NaN	0.000	0.408	NaN	-0.096	1.000	0.000	NaN	0.000	NaN	NaN	0.000
supplier_ids	1.000	0.709	0.000	0.000	0.000	0.000	0.000	0.000	0.287	0.000	0.000	0.428	0.163	0.000	0.000	0.000	0.000	0.000	0.000	0.246	0.000	0.000	0.000	0.000	0.000	0.000	0.427	0.000	0.000	0.000	0.000	0.000	1.000	0.298	0.000	0.000	0.000	0.000
target_level	1.000	0.392	0.000	NaN	NaN	0.000	NaN	0.000	0.181	NaN	0.000	-0.112	0.987	NaN	0.000	0.000	NaN	NaN	NaN	0.938	0.000	0.000	0.000	0.000	0.000	NaN	-0.153	0.000	0.000	NaN	NaN	NaN	0.298	1.000	0.000	NaN	NaN	0.000
transaction_type	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.500	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.075	0.000	0.238	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000	0.000	0.000	0.000
unit_cost	1.000	0.000	0.000	NaN	NaN	0.000	NaN	0.000	-0.028	-0.153	0.000	NaN	NaN	NaN	0.000	0.000	-0.110	0.093	0.020	NaN	0.000	0.000	0.000	0.000	0.000	NaN	NaN	0.000	0.000	NaN	NaN	NaN	0.000	NaN	0.000	1.000	NaN	0.000
unit_price	1.000	0.000	0.000	NaN	NaN	0.000	NaN	0.000	0.115	0.158	0.000	NaN	NaN	0.160	0.000	0.000	-0.335	0.101	-0.040	NaN	0.000	0.000	0.000	0.000	0.000	NaN	NaN	0.000	0.000	NaN	NaN	NaN	0.000	NaN	0.000	NaN	1.000	0.000
web_page	1.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	1.000

Missing values

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

	employee_id	privilege_id	__table_name__	id	company	last_name	first_name	email_address	job_title	business_phone	home_phone	mobile_phone	fax_number	address	city	state_province	zip_postal_code	country_region	web_page	notes	attachments	type_name	transaction_type	transaction_created_date	transaction_modified_date	product_id	quantity	purchase_order_id	customer_order_id	comments	order_id	invoice_date	due_date	tax	shipping	amount_due	unit_price	discount	status_id	date_allocated	inventory_id	status	customer_id	order_date	shipped_date	shipper_id	ship_name	ship_address	ship_city	ship_state_province	ship_zip_postal_code	ship_country_region	shipping_fee	taxes	payment_type	paid_date	tax_rate	tax_status_id	status_name	tax_status_name	privilege_name	supplier_ids	product_code	product_name	description	standard_cost	list_price	reorder_level	target_level	quantity_per_unit	discontinued	minimum_reorder_quantity	category	unit_cost	date_received	posted_to_inventory	supplier_id	created_by	submitted_date	creation_date	expected_date	payment_date	payment_amount	payment_method	approved_by	approved_date	submitted_by	group_by	display	title	filter_row_source	default	string_id	string_data
0	2	2	employee_privileges	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
1	<NA>	<NA>	employees	8	Northwind Traders	Giussani	Laura	laura@northwindtraders.com	Sales Coordinator	(123)555-0100	(123)555-0102	None	(123)555-0103	123 8th Avenue	Redmond	WA	99999	USA	http://northwindtraders.com#http://northwindtraders.com/#	Reads and writes French.		NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
2	<NA>	<NA>	employees	5	Northwind Traders	Thorpe	Steven	steven@northwindtraders.com	Sales Manager	(123)555-0100	(123)555-0102	None	(123)555-0103	123 5th Avenue	Seattle	WA	99999	USA	http://northwindtraders.com#http://northwindtraders.com/#	Joined the company as a sales representative and was promoted to sales manager. Fluent in French.		NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
3	<NA>	<NA>	employees	7	Northwind Traders	Zare	Robert	robert@northwindtraders.com	Sales Representative	(123)555-0100	(123)555-0102	None	(123)555-0103	123 7th Avenue	Seattle	WA	99999	USA	http://northwindtraders.com#http://northwindtraders.com/#	None		NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
4	<NA>	<NA>	employees	1	Northwind Traders	Freehafer	Nancy	nancy@northwindtraders.com	Sales Representative	(123)555-0100	(123)555-0102	None	(123)555-0103	123 1st Avenue	Seattle	WA	99999	USA	#http://northwindtraders.com#	None		NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
5	<NA>	<NA>	employees	6	Northwind Traders	Neipper	Michael	michael@northwindtraders.com	Sales Representative	(123)555-0100	(123)555-0102	None	(123)555-0103	123 6th Avenue	Redmond	WA	99999	USA	http://northwindtraders.com#http://northwindtraders.com/#	Fluent in Japanese and can read and write French, Portuguese, and Spanish.		NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
6	<NA>	<NA>	employees	3	Northwind Traders	Kotas	Jan	jan@northwindtraders.com	Sales Representative	(123)555-0100	(123)555-0102	None	(123)555-0103	123 3rd Avenue	Redmond	WA	99999	USA	http://northwindtraders.com#http://northwindtraders.com/#	Was hired as a sales associate and was promoted to sales representative.		NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
7	<NA>	<NA>	employees	4	Northwind Traders	Sergienko	Mariya	mariya@northwindtraders.com	Sales Representative	(123)555-0100	(123)555-0102	None	(123)555-0103	123 4th Avenue	Kirkland	WA	99999	USA	http://northwindtraders.com#http://northwindtraders.com/#	None		NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
8	<NA>	<NA>	employees	2	Northwind Traders	Cencini	Andrew	andrew@northwindtraders.com	Vice President, Sales	(123)555-0100	(123)555-0102	None	(123)555-0103	123 2nd Avenue	Bellevue	WA	99999	USA	http://northwindtraders.com#http://northwindtraders.com/#	Joined the company as a sales representative, was promoted to sales manager and was then named vice president of sales.		NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
9	<NA>	<NA>	employees	9	Northwind Traders	Hellung-Larsen	Anne	anne@northwindtraders.com	Sales Representative	(123)555-0100	(123)555-0102	None	(123)555-0103	123 9th Avenue	Seattle	WA	99999	USA	http://northwindtraders.com#http://northwindtraders.com/#	Fluent in French and German.		NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN

	employee_id	privilege_id	__table_name__	id	company	last_name	first_name	email_address	job_title	business_phone	home_phone	mobile_phone	fax_number	address	city	state_province	zip_postal_code	country_region	web_page	notes	type_name	transaction_type	transaction_created_date	transaction_modified_date	product_id	quantity	purchase_order_id	customer_order_id	comments	order_id	invoice_date	due_date	tax	shipping	amount_due	unit_price	discount	status_id	date_allocated	inventory_id	status	customer_id	order_date	shipped_date	shipper_id	ship_name	ship_address	ship_city	ship_state_province	ship_zip_postal_code	ship_country_region	shipping_fee	taxes	payment_type	paid_date	tax_rate	tax_status_id	status_name	tax_status_name	privilege_name	supplier_ids	product_code	product_name	description	standard_cost	list_price	reorder_level	target_level	quantity_per_unit	discontinued	minimum_reorder_quantity	category	unit_cost	date_received	posted_to_inventory	supplier_id	created_by	submitted_date	creation_date	expected_date	payment_date	payment_amount	payment_method	approved_by	approved_date	submitted_by	group_by	display	title	filter_row_source	default	string_id	string_data
502	<NA>	<NA>	customer	23	Company W	Entin	Michael	None	Purchasing Manager	(123)555-0100	None	None	(123)555-0101	789 23th Street	Portland	OR	99999	USA	None	None	NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
503	<NA>	<NA>	customer	13	Company M	Ludick	Andre	None	Purchasing Representative	(123)555-0100	None	None	(123)555-0101	456 13th Street	Memphis	TN	99999	USA	None	None	NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
504	<NA>	<NA>	customer	28	Company BB	Raghav	Amritansh	None	Purchasing Manager	(123)555-0100	None	None	(123)555-0101	789 28th Street	Memphis	TN	99999	USA	None	None	NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
505	<NA>	<NA>	customer	9	Company I	Mortensen	Sven	None	Purchasing Manager	(123)555-0100	None	None	(123)555-0101	123 9th Street	Salt Lake City	UT	99999	USA	None	None	NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
506	<NA>	<NA>	customer	24	Company X	Hasselberg	Jonas	None	Owner	(123)555-0100	None	None	(123)555-0101	789 24th Street	Salt Lake City	UT	99999	USA	None	None	NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
507	<NA>	<NA>	customer	1	Company A	Bedecs	Anna	None	Owner	(123)555-0100	None	None	(123)555-0101	123 1st Street	Seattle	WA	99999	USA	None	None	NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
508	<NA>	<NA>	customer	1	Company A	Bedecs	Anna	None	Owner	(123)555-0100	None	None	(123)555-0101	123 1st Street	Seattle	WA	99999	USA	None	None	NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
509	<NA>	<NA>	customer	17	Company Q	Bagel	Jean Philippe	None	Owner	(123)555-0100	None	None	(123)555-0101	456 17th Street	Seattle	WA	99999	USA	None	None	NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
510	<NA>	<NA>	customer	6	Company F	Pérez-Olaeta	Francisco	None	Purchasing Manager	(123)555-0100	None	None	(123)555-0101	123 6th Street	Milwaukee	WI	99999	USA	None	None	NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN
511	<NA>	<NA>	customer	22	Company V	Ramos	Luciana	None	Purchasing Assistant	(123)555-0100	None	None	(123)555-0101	789 22th Street	Milwaukee	WI	99999	USA	None	None	NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	NaT	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN

Duplicate rows

Most frequently occurring

	employee_id	privilege_id	__table_name__	id	company	last_name	first_name	email_address	job_title	business_phone	home_phone	fax_number	address	city	state_province	zip_postal_code	country_region	web_page	notes	attachments	type_name	transaction_type	transaction_created_date	transaction_modified_date	product_id	quantity	purchase_order_id	comments	order_id	invoice_date	tax	shipping	amount_due	unit_price	discount	status_id	inventory_id	status	customer_id	order_date	shipped_date	shipper_id	ship_name	ship_address	ship_city	ship_state_province	ship_zip_postal_code	ship_country_region	shipping_fee	taxes	payment_type	paid_date	tax_rate	status_name	tax_status_name	privilege_name	supplier_ids	product_code	product_name	standard_cost	list_price	reorder_level	target_level	quantity_per_unit	discontinued	minimum_reorder_quantity	category	unit_cost	date_received	posted_to_inventory	supplier_id	created_by	submitted_date	creation_date	payment_amount	payment_method	approved_by	approved_date	submitted_by	group_by	display	title	filter_row_source	default	string_id	string_data	# duplicates
0	<NA>	<NA>	customer	1	Company A	Bedecs	Anna	NaN	Owner	(123)555-0100	NaN	(123)555-0101	123 1st Street	Seattle	WA	99999	USA	NaN	NaN		NaN	<NA>	NaT	NaT	<NA>	<NA>	<NA>	NaN	<NA>	NaT	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	NaT	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaT	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	<NA>	<NA>	NaN	<NA>	<NA>	NaN	NaN	NaT	<NA>	<NA>	<NA>	NaT	NaT	NaN	NaN	<NA>	NaT	<NA>	NaN	NaN	NaN	NaN	NaN	<NA>	NaN	2

Overview

Variables

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values